Investigation of the amount of erosion at the upper Miocene unconformity in the southeastern part of the Malay Basin (2008)

IMPERIAL COLLEGE LONDON

(University of London)

Department of Earth Science and Engineering

Centre for Petroleum Studies

Investigation of the amount of erosion at the upper Miocene unconformity in the southeastern
part of the Malay Basin

by

Lune Gene Yeo

A report submitted in partial fulfillment of the requirements for

the degree of MSc Petroleum Geoscience

September 2008

DECLARATION OF OWN WORK

I declare that this thesis is entirely my own work and that where any material could be construed
as the work of others, this has been fully cited and referenced, and/or with appropriate
acknowledgement given.

Signature:.....................................................................................................

Name of student: LUNE GENE YEO

Name of supervisors: Professor Howard Johnson, Imperial College, London

Dr. Jamaal Hoesni, Petronas Research, Bangi (Malaysia)

ABSTRACT

Erosion magnitude estimation is a vital step in understanding petroleum systems. The Malay
Basin offshore Peninsular Malaysia underwent an inversion period in the late Miocene, which
led to erosion and the subsequent creation of a basin-wide unconformity. The erosion is
greatest in the southeast part of the basin, which forms the area of investigation for this study.

The erosion at given wells in the study area was quantified using compaction techniques
comparing compaction trends to a normal trend (of sonic transit time data), and a tectonic
method comparing backstripped basement depths to theoretically predicted basement depths.
There is a good correlation between the results from the compaction and tectonic methods;
although it was found that different methods are more suitable under different conditions.

The contour maps plotted from these estimates were found to tie in well with palaeo-geographic
maps with high erosion (up to 1400 m) at the basin margin in the southeast. The maps also
supported the theory that inversion was initiated by the rotation of Borneo.

The erosion thicknesses in the southeast Malay Basin were found to have little effect on
hydrocarbon generation timings, hastened the onset of thermal maturity, terminated expulsion
early for some wells and induced strata parallel hydrocarbon migration while reducing vertical
migration.

The aforementioned results can be further utilized in more wide-scale basin studies combined
with reservoir modeling in order to identify new petroleum systems or better understand existing
ones. This can lead to the discovery of new prospects for drilling.

ACKNOWLEDGEMENTS

I appreciate the opportunity provided by PETRONAS Research to work on data from the Malay
Basin. I would like to thank Dr. Jamaal Hoesni and Prof. Howard Johnson for their invaluable
guidance; and my parents for making geoscience a possibility for me.

“Our world has had many lives.”

Antares, Tanah Tujuh

TABLE OF CONTENTS

1. Introduction 1
1.1 Aims.................................................................................................................................. 1
1.2 Geological Setting: Malay Basin ........................................................................................ 1
1.3 Available Dataset .............................................................................................................. 6
2. Literature Review – The Determination of Erosion and Its Effects 7
2.1 Compaction Based Methods ............................................................................................ 7
2.2 Thermal History Based Methods .................................................................................... 11
2.3 Tectonic Based Methods................................................................................................ 12
2.4 Stratigraphic Based Methods ......................................................................................... 13
2.4 Previous Work................................................................................................................ 13
3. Methodology 14
3.1 Well Conditioning ............................................................................................................ 14
3.2 Constructing Normal Compaction Trends........................................................................ 16
3.3 Thermal Method .............................................................................................................. 20
3.4 Tectonic Method ............................................................................................................. 20
3.5 1D and 2D Basin Modeling ............................................................................................. 21
4. Results 24
4.1 Normal Compaction Curves ............................................................................................ 24
4.2 Exhumation Estimations From Compaction Methods ...................................................... 27
4.3 Exhumation Estimations From Thermal and Tectonic Methods ....................................... 28
4.4 Final Erosion Values ....................................................................................................... 29
4.5 Basin Models .................................................................................................................. 30
5. Discussion 31
5.1 Comparison of Methods .................................................................................................. 31
5.2 Erosion Trends ............................................................................................................... 35
5.3 Possible Causes of Inversion .......................................................................................... 38
5.4 Petroleum System Implications ....................................................................................... 42
6. Conclusions and Recommendations 52
7. References 53
Appendix 1 – Erosion Estimation i
Appendix 2 – Basin Modeling vi

TABLES, FIGURES AND ENCLOSURES
Table 1.1: Dataset ...................................................................................................................... 6
Table 3.1: Measured SBHT and corrected SBHT ..................................................................... 22
Table 4.1: True exhumation estimates for all wells from compaction methods.......................... 28
Table 4.2: True exhumation estimates for Well 10 from the tectonic and compaction methods 28
Table 4.3: True exhumation estimates for all wells from the tectonic method ........................... 29
Table 4.4: Final erosion estimates for all wells ......................................................................... 29
Table 4.5: Different erosion magnitudes used in 1D basin modeling ........................................ 30
Table 5.1: Formations present in Wells 8 and 13 ...................................................................... 34
Table 5.2: Timing of regional tectonic events............................................................................ 41
Table 5.3: Change in the timing of the onset of thermal maturity .............................................. 43

Figure 1.1: Location of the study area ........................................................................................ 1
Figure 1.2: Malay Basin stratigraphic column ............................................................................. 2
Figure 1.3: Kinematic evolution shear models ............................................................................ 3
Figure 1.4: Cross-sections.......................................................................................................... 5
Figure 2.1: Porosity-depth trends for sands and shales .............................................................. 9
Figure 2.2: Interval transit time evolution .................................................................................. 10
Figure 2.3: Thermal methods ................................................................................................... 12
Figure 2.4: Tectonic methods ................................................................................................... 13
Figure 3.1: Well conditioning workflow...................................................................................... 15
Figure 3.2: Well tops ................................................................................................................ 15
Figure 3.3: Well conditioning .................................................................................................... 16
Figure 3.4: Least squares regression ....................................................................................... 17
Figure 3.5: Windowed averaging .............................................................................................. 18
Figure 3.6: Subsidence curves ................................................................................................. 20
Figure 4.1: Heasler normal compaction curves ......................................................................... 24
Figure 4.2: Final Heasler curve................................................................................................. 25
Figure 4.3: Hillis normal compaction curves ............................................................................. 26
Figure 4.4: Heasler true exhumation......................................................................................... 27
Figure 4.5: Hillis true exhumation ............................................................................................. 27
Figure 5.1: Stretch factor versus basement depths................................................................... 32
Figure 5.2: Exhumation map overlays ...................................................................................... 36
Figure 5.3: Erosion maps ......................................................................................................... 37
Figure 5.4: Tectonic models ..................................................................................................... 40
Figure 5.5: Inversion mechanisms ............................................................................................ 41

Figure 5.6: I and K maturity points ............................................................................................ 43
Figure 5.7: L and M maturity points .......................................................................................... 44
Figure 5.8: Burial-maturity: Wells 8 and 10 ............................................................................... 45
Figure 5.9: Well 8 event charts ................................................................................................. 46
Figure 5.10: Well 11 and 14 event charts ................................................................................. 47
Figure 5.11: Well 10 and 13 event charts ................................................................................. 48
Figure 5.12: Hydrocarbon saturation: low case erosion ............................................................ 49
Figure 5.13: Hydrocarbon saturation: best case erosion ........................................................... 49
Figure 5.14: Hydrocarbon saturation: high case erosion ........................................................... 50

Enclosure 1.1: Khalid method .......................................................................................................i
Enclosure 1.2: Thermal method for Wells 2 and 4 ........................................................................i
Enclosure 1.3: McKenzie formula ................................................................................................ ii
Enclosure 1.4: Heasler method histograms ................................................................................ iii
Enclosure 1.5: Hillis method histograms ..................................................................................... iv
Enclosure 1.6: Erosion estimates from seismic section ...............................................................v
Enclosure 2.1: Eustasy curve and SWIT .................................................................................... vi
Enclosures 2.2 to 2.4: Thermal fits ............................................................................................. vi
Enclosures 2.5 to 2.11: Burial-maturity ....................................................................................... ix
Enclosure 2.12: Event charts .................................................................................................... xvi
Enclosure 2.13: Change in peak hydrocarbon generation timings ........................................... xvii
Enclosure 2.14: Maximum hydrocarbons generated ................................................................ xvii

Investigation of the amount of erosion at the upper Miocene unconformity in the southeastern part of the Malay Basin

Lune Gene Yeo, MSc Petroleum Geoscience, Department of Earth Science and Engineering

*Locations classified: Following the agreement with PETRONAS, field location names cannot be
revealed in this report or the associated presentation or poster.

1. INTRODUCTION

1.1 Aims

The aims of this study are to quantify and map the amount of erosion at the upper Miocene
unconformity in the southeastern part of the Malay Basin; and determine the effects of the
erosion thicknesses on the generation and migration of hydrocarbons.

1.2 Geological Setting: Malay Basin

The Malay Basin is an elongate intra-continental pull apart basin, about 250 km long and 250
km wide, located at the centre of Sundaland, the cratonic core of Southeast Asia (Figure 1.1), a
region where three converging lithospheric plates interact: the India-Australian, Eurasian and
Pacific plates (Hall, 1996).

Figure 1.1 – Location of the
southeastern part of the Malay Basin
(study area), wells and cross-sections
(modified from USGS, 1999) within
Southeast Asia (inset map).

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The Malay Basin was subjected to three main tectonic events: i) late Eocene to Oligocene (syn-
rift) extension and subsidence, ii) early to middle Miocene thermal subsidence (early post-rift)
accompanied by middle to late Miocene basin inversion and iii) late Miocene to Recent
subsidence (late post-rift) (Madon and Watts, 1998).

The basin fill (over 14 km thick in total) is subdivided via seismic stratigraphy into Units A to M,
from top to bottom (Madon and Watts, 1998). See Figure 1.2 for event timings relative to the
stratigraphic formations.

Figure 1.2 – Stratigraphy, hydrocarbon occurrences, source rocks and structural history of the
Malay Basin (after EPIC, 1997)
1.2.1 Basin Extension (Syn-rift) – 35 to 25 Ma

Geophysical studies around the Natuna Islands (Ben-Avraham and Emery, 1973) have shown
that the region is underlain by relatively thin continental crust (about 21 km thick). Most workers
therefore believe that the Malay Basin was formed by crustal or lithospheric extension.

White and Wing (1978) suggested that it was formed by the collapse of a regionally thinned
continental crust. Some authors suggested a major role for strike slip tectonics in basin
development. The occurrence of E-trending en-echelon anticlines in the basin has led Hamilton
(1979) to postulate that the Malay Basin may have been formed by right lateral wrenching.
Kingston et al. (1983) interpreted the Malay Basin as a wrench or shear basin formed by the
oblique subduction of the Indian plate beneath the Southeast Asia lithosphere along the
Sumatra-Java arc-trench system. Another common view is that the basins are pull-aparts along

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major strike –slip faults related to the India-Asia collision during the late Eocene (Tapponnier et
al., 1982; Daines, 1985; Polachan and Sattayarak, 1989).

More recent studies on the Malay Basin (Ngah et al., 1996; Tjia and Liew, 1996; Madon et al.,
1997) have adopted the extrusion tectonics model but emphasized the importance of pre-
existing basement faults in controlling basin development. Ngah et. al (1996), in particular, have
proposed that the basins were formed initially as aulacogens above a Late Cretaceous hotspot
and later developed into wrench or pull apart basins when their bounding faults were reactivated
as strike-slip faults due to the extrusion tectonics.

Heat flow data from the Malay Basin (Halim, 1994) indicate abnormally high heat flows (>100
mW m-2) that are characteristic of rift basins. Extensional structures associated with the basin
formation include half grabens that are bounded by major normal faults and filled by non-marine
synrift sediments. The onlapping geometry of the postrift strata (Units L and younger) at the
basin margins (Madon and Watts, 1998) is characteristic of basins formed by lithospheric
stretching (Dewey, 1982).

Madon (1997) suggests kinematic models for the extension and inversion of the Malay Basin
(Figure 1.3), where the basin opening and inversion are due to sinistral and dextral shear of a
broad NW-trending deformation zone, which Tjia (1994) referred to as the Axial Malay Fault
Zone.

Figure 1.3 – Shear model for the
kinematic evolution of the Malay Basin
(after Madon, 1997)

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Cross sections of the basin, such as in Figure 1.4, show the “steer’s head” geometry of a typical
rift-sag couplet (Dewey, 1982); which is widely attributed to McKenzie’s 1978 uniform stretching
model. In such a model, initial rifting of the brittle upper crust results in fault controlled
subsidence; followed by a later sag phase which represents the thermal subsidence as the
thermal anomaly associated with lithospheric stretching decays. The gentle inward tilting of the
basin flanks, however, suggests a combination of thermal and flexural subsidence of the basin
flanks.

During the extensional phase, E-trending half grabens were formed and filled by braided-fluvial
and lacustrine sands and shales, with increasing lacustrine influence towards the basin centers;
represented by Units M and older (Figure 1.2) (Lovell et al., 1994).

1.2.2 Basin Thermal Subsidence Followed by Inversion (Early Post-rift) – 25 to 10.5 Ma

In the following period of post-rift thermal subsidence, the depositional environment initially
changed to marginal marine. Lower Miocene progradational and aggradational fluvial to tidally-
dominated estuarine sediments were replaced by shallow marine sediments as relative sea
level continued to rise in the middle Miocene (Figure 1.2).

Dextral shear on the Axial Malay Fault Zone during the middle to late Miocene resulted in the
inversion of the Malay Basin. Compressional deformation caused the reactivation and hence,
transpressional deformation of those earlier basement faults, which resulted in the E-trending
wrench-fault anticlines and pop-up structures (Madon et al., 1999). In the basin center, there are
numerous faults that originate in the basement but propagate up-section into the overlying
strata: interpreted as basement extensional faults that were reactivated during the
transpression/inversion event (Madon, 2007).

The EPIC (1994) study shows that the peak of fold growth is earlier in the south than in the
north, despite the timing of structural growth being generally synchronous across the whole
basin. Syn-inversion stratigraphic units thin towards the crestal region of the inversion
structures.

The basement uplift in the south-eastern (and likely the southwestern) Malay Basin, which led to
the erosion and development of an upper Miocene regional unconformity (Ismail et al., 1994;
Madon et al., 1999) is attributed to this regional deformation event (Madon, 1997).
Unconformities represent hiatuses in sedimentation caused by changes in relative base level
due to tectonic uplift (as in this case), or relative sea level fall. This hiatus period which created
the Upper Miocene Unconformity (UMU) is postulated by Madon (1998) to be between 8.5 to 7
Ma. This timing, however, is inconsistent with the timing of the unconformity in the widely used
EPIC (1994) stratigraphic column, which puts it at 10.5 Ma (Figure 1.2).

Inversion was greatest in the southeast and center of the basin, where erosion may have
provided a sediment source for the northern part of the basin. The UMU, which overlies the D
formation truncates folded and uplifted syn-rift to early post-rift strata (Madon and Watts, 1998)
(Figure 1.4) and represents a regional marine transgression in the Malay Basin
(Watcharanantakul and Morley, 2000).

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71km

B W E

21km

Figure 1.4 – Cross-sections A and B of the Malay Basin. The interpreted seismic cross-section
was obtained via personal communication with J. Hoesni, 2008. For locations, see Figure 1.1.

The formations deposited during this period are units L to D. Units L to K were deposited under
fluvial – lacustrine settings. Formations I and J consist of progradational to aggradational fluvial
to tidally dominated estuarine sands.

At the start of the inversion, unit H was deposited in deltaic to shallow marine settings and
include coals and coaly shales. Strata of the overlying middle Miocene H Group through upper
Miocene D Group were deposited during alternating marine transgressions and regressions
(Tjia and Liew, 1996). Formations H and F are composed of dominantly marine to deltaic
sediments with fluvial and estuarine channels, which include coals and coaly shales, deposited
during an overall sea level rise. Groups E and D were deposited by the progradational stacking
of dominantly fluvial and estuarine channels; and culminated with the UMU.

Deformation was contemporaneous with sedimentation, such that erosion and non-deposition
on the crests on inversion structures occurred simultaneously with deposition on the flanks.

Although basin inversion caused wholesale uplift and formation of flower structures, on a basin
scale the subsidence accelerated.

1.2.3 Basin Subsidence (Late Post-rift) – 10.5 Ma to Present

In the latest Miocene-Pliocene, a tectonically quiescent period, regional subsidence resumed.

Fully open marine conditions were established, with undeformed clays and silts (Formations A
and B) deposited over the UMU; in an overall marine transgressive cycle of sedimentation in
nearshore to shallow marine environments.

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1.3 Available Dataset

The dataset for this study (Table 1.1) was provided courtesy of PETRONAS Research.

Well Data Type
Names Table 1.1 Available dataset
Well 1 Sonic GR SP Calliper VR/SBHT TOC
Well 2 Sonic GR Calliper VR/SBHT TOC
Well 3 Sonic GR SP Calliper VR/SBHT
Well 4 Sonic GR SP Calliper VR
Well 5 Sonic GR VR
Well 6 Sonic GR Calliper VR
Well 8 Sonic GR SP Calliper VR TOC/HI
Well 9 Sonic GR SP Calliper
Well 10 Sonic GR SP VR
Well 11 GR SP Calliper VR
Well 12 Sonic GR SP Calliper VR
**Note that the vitrinite reflectance data for the individual wells are a combination of data from
wells in the same fields.

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2. LITERATURE REVIEW – THE DETERMINATION OF EROSION AND ITS EFFECTS

Exhumation is defined as the displacement of rocks with respect to the surface whereas erosion
refers not only to the process of elevating rocks with respect to the surface, but also to the
removal and transport of weathered material. Only removed rocks are eroded; but the entire
rock column is exhumed as a result of erosion (Hillis, 1995).

Exhumation can be determined using the techniques outlined below with emphasis is placed on
compaction technique, the main technique used in this study. As published methods of
differentiating erosion and exhumation values were not found to be available, exhumation
magnitudes given by the methods below were taken to be erosion magnitudes. Thus, when
referring to erosion estimates in this study, both terms are used interchangeably.

2.1 Compaction Based Methods

2.1.1 A Definition of Compaction

Compaction is the reduction of sediment volume during burial due to mechanical and thermo-
chemical processes (Bulat and Stoker, 1987; Sclater and Christie, 1980; Magara 1976). The
resulting matrix reorganization causes an increase in bulk density and a decrease in interval
transit time.

Mechanical compaction starts immediately after deposition and is caused by the closer packing
of grains due to increased vertical stress with depth. Chemical compaction is a result of the
dissolution and precipitation of minerals (and hence matrix reorganization) and is mainly
controlled by temperature (Bjørlykke, 1999). Cement precipitation near grain contacts increase
the rigidity of the grains, and when rock strength exceeds the vertical stress, mechanical
compaction ceases. At this point the porosity of the clastic unit is zero and the density and sonic
interval transit time measured represent the rock matrix values.

Both mechanical and chemical components therefore make up any compaction with depth
trend. The influence of the chemical component is difficult to quantify, although the mechanical
aspect is straightforward to estimate.

Since the original volume of a sedimentary unit of a given age is not known, the amount of
compaction cannot be measure directly. Instead, compaction must be computed from measures
of changes in porosity, or a proxy thereof.

If porosity determinations form the basis of the technique, it must be assumed that all reduction
in pore space is caused by mechanical, and not chemical, compaction. This can be determined
from the measurement of either shale or sand compaction.

2.1.2 Compaction Data Types

Sonic, density and neutron well logs are proxies for porosity; and as such are used to represent
compaction with depth trends. The density tool, however has a shallow depth of penetration
(approximately one foot), and is thus greatly influenced by borehole wall conditions and mud
cake thickness. Thus, it effectively measures the density of the flushed zone.

The neutron porosity tool measures the effect of the formation on fast neutrons emitted by a
source, where hydrogen has the biggest effect in slowing down and capturing neutrons.

7



However, neutron log is calibrated to read the correct porosity assuming the pores are filled with
fresh water for a given matrix; and is strongly affected by the presence of clays and gas.

The sonic tool measures the time taken for a compressional; wave to travel form the transmitter
through the formation to the receiver at the either end of the tool. This tool has a greater depth
of penetration and thus is not so adversely affected by borehole conditions. It does not respond
to secondary porosity (fracture or vuggy porosity) as the emitted wave takes the fastest travel
route from the transmitter to the receiver; thus making it an ideal tool for measuring the
compaction of shales and sands which is chiefly a function of primary porosity. Due to the
factors outlined above, the sonic log was used in this study.

2.2.2 Compaction Relationships

There are number of porosity-depth functions available, the simplest of which is a linear
decrease in porosity with depth as assumed by authors such as Hillis, 1995; Hillis and
Mavromatidis 2005 and Storvoll et al., 2005. This trend has been proven to fit porosity-depth
data in units over finite depth intervals (Bulat and Stoker, 1987) and is typically observed in
sandstones (Magara, 1980). However a linear depth trend does not represent the exponential
trends observed in shallow depths at shales and implies negative porosities below a certain
depth. Direct porosity measurements of core plugs (sands) from an unexhumed section would
provide an empirical porosity depth relationship (Corcoran and Doré, 2005).

Most studies, such as those of Heasler and Kharitnova (1996), and Corcoran and Mecklenburgh
(2005); use shale only lithologies in their analysis as shales are not as susceptible to chemical
compaction compared to sands and carbonates (personal communication J. Hoesni, 2008), and
thus porosity decrease expressed mainly by mechanical compaction, which is 95% according to
Taylor (2007).

Athy (1930) developed an exponential function for porosity with depth, which is more
representative of measured compaction trends within shale units (Figure 2.1)

Athy’s equation is given as

Ø = Øoe-bx …….. (2.1)

where Ø = porosity at depth x, Øo = porosity of unconsolidated sediments at the
depositional surface (mudline) and b = lithology dependent compaction coefficient which
determines the slope of the porosity versus depth trend.

8



Figure 2.1 – Typical porosity-depth trends for
sandstones and shales (after Magara, 1980)

This equation proposes that porosity decreases exponentially with depth as do the interval
transit time. Most authors, such as Heasler and Kharitnova (1996) agree that the transit time
trend must approach a finite value with depth and as a result adopt equation 2.1.

In this study, both shale and sand lithologies are used for compaction analysis to maximize the
amount of constraints on the results.

2.2.3 Determining Exhumation

Exhumation (and in effect erosion) can be determined from compaction analysis where a plot of
porosity versus depth for a “normally compacted” un-exhumed succession within the basin must
first be generated, which requires a significant number of porosity measurements at maximum
burial. Where localized exhumation is dominant, this can be approximated from a sonic log of an
unexhumed well; but this must be approximated form nearby unexhumed basins if there is
regional exhumation as was done by Corcoran and Mecklenburgh, 2005.

After this “normal compaction” trend has been established, porosity depth trends can be
determined for individual well locations and compared with the reference curve. Apparent
exhumation refers to the elevation for exhumed sedimentary rocks in the well under
investigation above their maximum burial depth in the normally compacted well, and is given by
the displacement, along depth axis, of the observed compaction trend from the normal
compaction trend (Figure 2.2).

Post-exhumation burial, however, perturbs the compaction trend, creating the facade of less
erosion than in actuality as apparent exhumation is only equal to true exhumation where there
has been no post-exhumation burial (Figure 2.2).

9



Figure 2.2 – Interval transit time evolution during burial (A), subsequent uplift and exhumation
(B) and post-exhumational burial (C, D and E). The apparent exhumation (EA) is the amount of
exhumation not reversed by subsequent burial. It can be measured by displacement along the
depth axis of the transit time relationship of the exhumed sequence (B or C) from that of a
reference of normally compacted sequence (A, D or E) (after Hillis, 2005)

The compaction technique operates on the fundamental assumptions that porosity ‘rebound’
magnitudes are negligible, as confirmed by laboratory tests and empirical observations (Giles et
al., 1998); and that all relevant stratigraphic units in the basin have experienced equilibrium
compaction with burial.

This technique is not applicable to sections with relatively high transit times due to other factors,
such as overpressure or hydrocarbon-filled porosities (Hillis, 1995).

2.2.4 Limitations of the Compaction Method

There are a number of limitations to using compaction techniques to determine exhumation:

i) The relationship between compressional velocity and porosity depends critically on lithology
(Storvoll et al., 2005)

ii) Unreliability in establishing the normal compaction trend for a basin or rock unit is a key
limitation, particularly in basins where regional exhumation has occurred, such as in the Malay
Basin.

iii) In hydrostatically pressured extensional basins, both effective stress and temperature
increase with burial depth, so it is generally uncertain whether compactional or thermal
processes are responsible for observed increase in velocity (decrease in transit time). The sonic

10



transit time method assumes that mechanical compaction is the dominant control on porosity
loss through burial, although this is not strictly the case.

iv) The technique is indecisive when there is a similar amount of post-exhumational burial to that
of the missing section at the UMU. The compaction trend from such a well would appear to be
normally compacted.

v) This method cannot be applied to overpressured sections, which have higher transit times
than in normal sections. The combination of the rapid burial of certain stratigraphic units
(especially Formations H to D) and uplift of initially normally pressure strata (Groups J to M) is
put forth by Singh and Ford (1982) as the common cause for widespread occurrence of
overpressures in the Malay Basin. In the basin centre, the onset of overpressure occurs in
stratigraphically younger formations (Formations E and F), but in the basin flanks, this is at
stratigraphically older horizons due to increasing sand percentage away from the centre. The
top of the overpressure usually coincides with the top of the oil window, suggesting a link
between hydrocarbon generation and the onset of overpressure.

2.2 Thermal History Based Methods

Thermal history based techniques for exhumation estimation provide information about the
movement of rocks relative to a thermal reference frame by utilizing the principle that
sedimentary rocks are heated as they are buried and cool as they are exhumed (Corcoran and
Doré, 2005). In a vertical succession of rocks, a maximum palaeo-temperature profile
interpreted from vitrinite reflectance (VR) or fission track analysis (FTA) (or a combination of the
two) can be used to estimate the palaeo-geotherm for that succession and, by extrapolation to
an assumed palaeo-surface temperature, the magnitude of exhumation at that location can be
determined (Figure 2.3). Two of the most prominent studies are those of Cavanagh et al. (2006)
and Green et al. (2002). This technique was used in this study to compare with results from the

11



tectonic and compaction techniques.

Figure 2.3 – Thermal history based methods. ∆z refers to exhumation amount (after Corcoran
and Doré, 2005)

2.3 Tectonic Based Methods

Corcoran and Doré (2005), describe a theoretical technique for assessing the magnitude of
exhumation in offshore basins, in which the uniform lithospheric stretching model of McKenzie
(1978) plays a major role. The model predicts an initial syn-rift, fault related subsidence followed
by an exponentially decreasing post-rift, thermal subsidence phase. McKenzie’s model
facilitates the determination of theoretical subsidence curves which can then be compared with
observed tectonic subsidence histories derived from the backstripping of sediment columns in
wellbores. The exhumation is determined by identifying locations where the modeled tectonic
subsidence is greater than the observed subsidence (Figure 2.4). This technique was used by
Rowley and White (1998) to inverse model extension and denudation in the East Irish Basin;
and will also be used in this study to compare with results from the thermal and compaction
techniques.

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Figure 2.4 – Tectonic subsidence analysis based methods. EG refers to true exhumation which
is a function of uplift (UT, UP) (after Corcoran and Doré, 2005)

2.4 Stratigraphic Based Techniques

Basic stratigraphic techniques of unconformity identification, section correlation, extrapolation
and restoration can offer a rationale for estimating the timing and magnitude of exhumation.
When using this technique, it is, however, hard to quantify exhumation in areas of epeirogenic
uplift and denudation; or varying original depositional thickness (Corcoran and Doré, 2005) such
as in the Malay Basin. Thus, this technique is not applicable in the context of this study.

2.5 Previous Work

Murphy (1989) estimated around 1200 m of the Miocene strata was eroded away in the Malay
Basin whereas Ramly (2004) estimated a range of 10 to 200 m of erosion in the southern
margin, while Ngah (1990) found up to 800m of erosion in the southeast.

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3. Methodology

Based on a review of literature, four chief methods are available to estimate exhumation. The
compaction method, however, serves the objective best due to reasons discussed in Section
5.1.

As both sand and shale sections are available from the Malay Basin, separate methods were
used to derive the normal compaction trends for each lithology. The method applied in Heasler
and Kharitnova (1996)’s erosion estimates study on the Bighorn Basin was used for the shale
sections; while the method used by Hillis (1995) was used for the sand sections. The reasons
behind these will be explained in Section 3.2. For the convenience of reference, the former
method will be referred to in the rest of this report as the Heasler method, while the latter will be
referred to as the Hillis method.

A tectonic method based on the description by Corcoran and Doré (2005) was used to further
constrain the resultant exhumation values; and calculate exhumation for Wells 4 and 11, which
is not suitable for the compaction method for reasons that will be explained in Section 3.2.

A thermal method using vitrinite reflectance is also used to provide values for comparison.

The approaches used to approximate exhumation in this study can be summarized as follows

1. Compaction methods

a) Shale sections – Heasler method

b) Sand sections – Hillis method

2. Tectonic method

3. Thermal method

3.1 Well Data Conditioning

In order to prepare each well for the establishment of a normal compaction trend and
subsequent exhumation analysis, conditioning must be applied so that analogous readings are
removed to ensure that the measurement points represent the true log properties of the shale or
sand units. Conditioning followed the process chart shown in Figure 3.1.

Figure 3.3 illustrates the type of features removed and the effects of conditioning that improves
the accuracy of exhumation estimates; and is related to the numbered steps in Figure 3.1.

As only vertical wells were present, the sub-seabed depths were converted directly from MDKB
(Measured Depths from Kelly Bushing). The formation tops in sub-seabed depths and Kelly
bushing depths for all wells is shown in Figure 3.2.

No attempt is made in this study to convert transit time to velocities or porosities, as the majority
of work on compaction trends to date is using interval transit time (Hillis, 1995; Corcoran and
Mecklenburgh, 2005; Heasler and Kharitnova, 1996 and others), and thus it was deemed
unnecessary.

14



Figure 3.1 - Well conditioning process flow

Figure 3.2 - Well Kelly Bushing depths and formation thicknesses

15



Figure 3.3 – Well conditioning process for Heasler method (Well 10). Conditioning for HIllis
method is similar with the exception of clean sands picked out instead of shales.

3.2 Constructing Normal Compaction Trends

3.2.1 Shale Sections – Heasler Method

Typical porosity depth trends for shales generally follow an exponential type curve as inscribed
by Magara (1980) (Figure 2.1). Thus for the shale sections of the Malay Basin, such a type of
curve was computed for the normal compaction trend using the Heasler method.

Following section 2.2.2, Athy’s (1930) compaction trend for shales was adapted for analysis of
interval transit time by Magara (1976), to give

DT = DToe-bx …….. (3.1)

where DT = transit time as measure by the sonic wireline tool, DTo = interval transit time
at the mudline, b = shale compaction coefficient and x = depth where the measurement
DT was recorded.

As equation 4.1 is not constrained at depth and transit time DT will trend to 0, Heasler and
Kharitnova (1996) have introduced a constant which is in effect the interval transit time of the
rock matrix.

DT = DToe-bx + C…….. (3.2)

16



where C is the asymptote of the exponential function, effectively the shift constant
applied to the dataset to take account of the points at maximum compaction.

The approach taken in this study expands on the fundamental assumption of Heasler and
Kharitnova (1996) that porosity reduction with depth in a heterolithic sedimentary sequence is
described by a single, average shale compaction coefficient, b; and uses different b values for
different depth intervals (See Section 4.1 page x)

In order to determine the “best fit” equation that describes the normal compaction trend for the
southwest Malay Basin, equation 3.2 was transformed logarithmically to

Ln(DT-C) - Ln(DTo) = -bx…….. (3.3)

A least squares regression (Figure 3.4) was used to find b, where regressions with different
values of C (C-trials) were run. By varying C and DT a series of b values were determined. The
set of parameters which give the maximum coefficient of determination, R2 (a value representing
the closeness of the fit to the dataset) represent the best-fit curve.

Figure 3.4 – Least squares regression fit for Well 2 data

Wells 1, 2, 5, 9 and 12 were picked to produce candidate normal compaction curves as these
well sections relatively unaffected to any erosion (formations A and B are intact), based on their
respective formation tops (Figure 3.2). Wells 3, 6, 8 and 10 were subjected to erosion as shown
by the formation tops (Figure 3.2) (and thus exhumation), Well 11 does not have any sonic log
data whereas Well 4 does not have any units logged below the UMU; and hence these wells
were excluded from the normal compaction curve derivation process.

The interval transit times of the (conditioned) shale sections were subjected to windowed
averaging (Figure 3.5) on the scales of every 10, 25, 50 and 100 meters from the seabed. A
windowed average of every 25 meters from the seabed was gauged to be the most
representative sonic log data curve, as it had minimal uncertainty range (noisiness of data) and
minimal loss of data trends due to upscaling.

17



Figure 3.5 – Windowed averaging every 25 m (Well 5)

Both data pre- and post-averaging were subjected to least squares regression analyses in order
to preserve a balance between the original and upscaled data. The best fit combination of the
two yielded suitable parameters C, b and DTo for each well. The final normal compaction curve
was picked out of a cross comparison of all curves generated by the aforementioned wells
(Section 4.1.1).

Estimates of exhumation would then be approximated by comparing this normal compaction
trend with the conditioned transit time data for each of the exhumed wells within the study area.
The difference between the depth of the computed normal compaction trend and the depth of
each measured transit time point in an exhumed well yielded a single estimate of apparent
exhumation given by the equation below:

Ln(DT - C N ) - Ln(DToN )
Apparent Exhumation = – xunderinvestigation…….. (3.4)
-b
where CN and DToN is the C-value and DTo value for the final normal compaction trend,
respectively and xunderinvestigation is the current sub-seabed depth where exhumation is
being calculated.

Exhumation using the Heasler method was calculated for all wells except for Well 11 (which has
no sonic log data) as all of them had clean shale sections.

Khalid’s Method:

A variation on the Heasler method was also carried out using the steps done by Ngah (1990),
which will be referred to Khalid’s method in this report. This method takes into account the
amount of exhumation undergone by after the formation of the unconformity (and hence
erosion), which is taken away from the true exhumation magnitudes calculated by the Heasler
method (Enclosure 1.1).

18



3.2.2 Sand Sections – Hillis Method

For sandstones, typical porosity depth trends are linear Magara (1980) and fit porosity depth
data in units over finite depth intervals as proven by Bulat and Stoker (1987). See Figure 2.1 for
comparison with a typical shale porosity depth trend.

The linear normal compaction trends over finite depth intervals (one per formation) as proposed
by Hillis (1995), which is the method used on the clean sand sections of the study area’s wells.

In an area subject to exhumation, the wells with the highest interval transit times (lowest
velocity) for their given burial depth should be taken to be normally compacted, provided their
relatively high transit times is not due to phenomena which may inhibit normal compaction such
as overpressure or hydrocarbon filled porosity. For a linear decrease with depth, any two or
more data points which can be linked by a straight line that has no points falling to its right less
compacted side, may potentially define normal compaction. This line is given by a general linear
line equation:

xunderinvestigation = mDT + c…….. (3.5)

where x = sub-seabed depth under investigation and DT = interval transit time for that
depth. The gradient and y-intercept of the line is given by m and c, respectively.

Eight such lines could be plotted for formations D, F, H, I, J, K, L and M (Section 4.1.2 - Figure
4.2) where the transit times for each formation is plotted from every well where a clean sand
interval was available for the formation under investigation. Individual m and c values were
derived for each formation.

Wells 1, 2, 5, 6, 8, 9 and 10 contain clean sand intervals and were thus exhumation estimates
using the Hillis method. The normally compacted interval transit time, DTN, can be found for
each well by rearranging equation 3.4 to the equation below:

x underinvestigation - c
DTN = …….. (3.6)
m
where m and c differs for each formation which was computed earlier by using equation
3.5.

Apparent exhumation is then the difference between DTN and the measured transit time for the
depth under investigation.

3.2.3 Estimating Exhumation Using Compaction Method

For each well under investigation, all the measured apparent exhumation values can be
characterized by standard descriptive statistics by plotting these in a histogram. It is then
possible to identify the mode. This is the most useful measure of the data as it gives the most
frequently occurring value of exhumation rather than the mean which also takes into account the
extreme high and low values which are not representative of the dataset as a whole.

This mode, however, does not represent the total (true) exhumation, as post-exhumation burial,
BP must be considered. The apparent exhumation, EA, calculated by the abovementioned
Heasler and Hillis methods therefore underestimates the exhumation and so all estimates must

19



have the thickness of post-exhumation burial added on. This was taken as the sub-seabed
thickness of sediment fill above the UMU for each well.

In error analysis, the most likely exhumation is the mode. However, the likelihood of getting
large values of exhumation is just as likely as getting a small value, so the percentiles are not
used. Instead, the deviation from the mode, which is well dependent, was computed to identify
the uncertainty range.

3.3 Thermal Method

Exhumation values for Wells 2 and 4 were calculated by applying the thermal method explained
in Section 2.2 on VR data for the respective wells. This was done using a combination of the
techniques used in Green et al. (2002), where the temperature profile derived from VR data was
compared with corrected SBHT data (see Section 3.4) for Well 2; and that in Gallagher (2008),
which involves analyzing discontinuities in the VR data at unconformities for Wells 2 and 4. See
Enclosure 1.2 for details. As this method does not play any role in determining the final
exhumation values, no detailed description on the thermal method is made.

3.4 Tectonic Method

The tectonic method approximates exhumation by comparing theoretical subsidence curves
(which varied with stretch factor) with observed tectonic subsidence histories derived from the
backstripping of sediment columns in wellbores (Figure 2.4).

Two approaches were considered for obtaining the theoretical curves. One was to calculate
initial synrift and subsequent thermal subsidence using a formula (Enclosure 1.3) described by
Allen and Allen (2005) based on McKenzie’s 1978 uniform stretching model.

Another method was to use preexisting subsidence curves at various wells in the Malay Basin
calculated by Madon and Watts (1998) (Figure 3.6), who used a constant strain-rate, finite-
rifting, uniform stretching model by Cochran (1983). A linear relationship was found between the
final basement depths of Madon and Watts (1998) and stretch factor (Section 5.1.2).

Figure 3.6 – Examples of predicted subsidence curves and stretch factor values from Madon
and Watts (1998)

20



In both approaches, timing of rifting was to have started in 35 Ma (Early Oligocene) and ended
at 25 Ma based on the age of the oldest sediment (Yakzan et al., 1994).

Water loaded sediment backstripping was then done for wells 10 and 11 as both these wells
have sonic log data that penetrate down to the basement. This was done through standard
basin modeling software (Petromod 1D Express) by inputting formation top depths and palaeo-
water depths. Backstripped curves were also available from several other locations in the
Malay Basin (Madon and Watts, 1998).

The difference between the theoretical curve basement depths and the water loaded basement
depths gives apparent exhumation magnitudes. Post-exhumation burial was then added on to
provide true exhumation. The magnitudes of exhumation approximated from comparison with
both the McKenzie and Cochran theoretical curves for Well 10.

The basement depths of Wells 10 and 11, as well as those of Madon and Watts (1998) were
then extrapolated to the other wells in the dataset using a map of the pre-Tertiary basement
depths as a rough guide.

An uncertainty of 0.1 in stretch factor was assumed for each of the well sections, which
translated into the uncertainties in exhumation in Section 4.3.

3.5 1D and 2D Basin Modeling

3.5.1 1D Modeling

1D basin modeling using the PetroMod (Express) software from Integrated Exploration Systems
(IES) was carried out for all wells to investigate the difference in petroleum generation
properties between uneroded sections and sections with erosion (values from the best
estimates).

Erosion estimates from Khalid’s method for Wells 9 and 12 displays a significant difference
compared to best estimates of erosion for these wells (Section 4.4). The same estimates for
other wells, including Well 5, do not display any significant difference (Section 4.4). Thus,
additional modeling was carried out for Wells 9 and 12 to investigate the effects of this
difference on the timing of hydrocarbon generation, and on Well 5 as a control (representing the
other wells).

As stated in Section 1.2.2, non-deposition on the crests of inversion structures occurred
simultaneously with deposition on the flanks. Thus, the models for Wells 1, 4, 8 and 11, which
are located on the crests are given periods of non deposition during the deposition of the
missing sections (8.5 to 7 Ma); whereas for other wells deposition was inputted to continue for
this period of time.

Total organic carbon (TOC) values and kerogen types for Wells 1, 2 and 8 were included in the
dataset, but those for Wells 9, 11 and 12 were obtained from nearby fields (*locations
classified). The HI and TOCs (for Pre-I group source rocks) for wells 5, 10 13 and 14 were
obtained from the Epic (1994). The source rock kinetic model used in this study is the Easy Ro
model of Sweeney and Burnham (1990).

Maturity-burial histories were generated for Wells 1, 2, 5, 8, 9, 10, 11, 12, 13 and 14; but not for
Wells 3, 4 and 6 as these wells do not have TOC information.

21



The sea level curve for all models was taken from the global eustasy curve as the relative sea
levels for the Malay Basin was similar to the global sea levels (personal communication J.
Hoesni). This was taken from Miller et al. (2005)’s interpretation of Haq’s eustasy curve
(Enclosure 2.1).

Vitrinite reflectance (VR) data was available for Wells 1, 2, 5, 8, 9, 10, 11 and 12 and single
bottom hole temperature (SBHT) for Wells 1 and 2. SBHT was corrected using the method
proposed by Waples and Mahadir (2001); given by the formula:

Tc = Ts + f X (Tm-Ts) …….. (3.7)

- 0.1462Ln(TSC) + 1.699
f= …….. (3.8)
0.572 × Z 0.075
where Tc = corrected temperature, Tm = measured temperature, Ts = surface
temperature, f = correction factor, TSC = time since circulation and Z = depth.

As Wells 13 and 14 had no VR or SBHT data, they were calibrated using VR and SBHT data
from Wells 8 and 5 respectively, as these were the nearest wells.

A McKenzie crustal stretching model (from PetroMod) was used to approximate the heat flow
history for the models. Rifting times and stretching factors were kept the same as in the
aforementioned tectonic method, but the duration of thermal subsidence was adjusted to fit the
corrected SBHT (Table 3.1) and VR data for each individual well (Enclosures 2.2 to 2.4).

TSC SBHT, Corrected Temperature,
Well Name Depth, Z (m) (hours) Tm (°C) f Ts (°C)
Well 1 985 9 57 1 70
1294 3 73 2 100
1381 3 74 2 100
1594 5 81 1 106
1734 4 79 1 105
1950 5 90 1 119
2212 5 97 1 128
2405 5 110 1 147
2498 5 118 1 157
Well 2 991 4 27 2 27
2395 6 96 1 124
Well 3 1161 7 74 1 96
1773 6 87 1 113
2162 11 118 1 147
2226 11 121 1 152
Surface Temperature, Ts = 27 °C
Table 3.1 – Measured SBHT and corrected SBHT (see equation 3.8 above)

Regional sediment water interface temperature (SWIT) values were obtained from PetroMod
(which uses values from Wygrala (1989) for Southeast Asia, latitude five (study area). Trap

22



formation timing was taken from field reports from the Malay Basin from C & C Reservoirs
(2008).

3.5.1 2D Modeling

2D modeling of a cross-section through Well 9 to Well 13 to Well 8 was accomplished using the
Temis2D software from Beicip Incorporated to investigate the effects of erosion on hydrocarbon
migration.

A cross-section was first digitized from an interpreted seismic cross-section (Figure 1.4B)
across the aforementioned wells, sourced via personal communication with J. Hoesni, 2008.
This was a laborious process involving manual data entry from interpreted horizons and faults in
the cross-section image into a format (.ext file) readable by Temis2D.

The eustasy, crustal model, lithology and source rock parameters were kept the same as in the
1D modeling. The bottom (of the basement) temperatures of the basin were kept as a constant
1333 °C, the temperature assumed for the Moho.

The source rock intervals for the cross-section modeled are formations I, K, L and M. The faults
were digitized from the cross-section (Figure 1.4B).

The faults were interpreted as open during the time of rifting and inversion (due to reactivation);
and closed at all other times.

23



4. RESULTS

4.1 Normal Compaction Curves

4.1.1 Heasler Method

From the normal shale compaction curves derived from Wells 1, 2, 5, 9 and 12 as shown in
Figure 4.1, the final normal compaction curve for the Malay Basin (Figure 4.2) was computed
using C (shift constant) and b (shale compaction coefficient) values from that of Well 2 for sub-
seabed depths of the interval 0 - 2329 m; and from that of Well 2 for 2330 - 2399 m. This was
done as the normal compaction curve generated from Well 2 had the highest interval transit
times from depths 0 to 2329 m, but for the interval 2330 - 2399 m, this was true for Well 12.

Figure 4.1 – Potential normal compaction curves from the Heasler method

24



Figure 4.2 – Final normal compaction curves from the Heasler method

Although normal compaction curves from Well 5 and Well 9 are shown to have higher transit
times, they were not used for the computation of the final normal compaction curve as the lines
of best fit through the logarithmically transformed data (see Equation 3.3) for these wells had a
low maximum coefficients of determination (poor fit).

As Figure 4.2 shows, the interval transit time in which the normally compacted curve intersects
the mudline (where sub-seabed depth = 0) is in the range of 180 to 200µs, in agreement with
Magara’s (1980) observations.

4.1.2 Hillis Method

As explained in Section 3.2.2, the normal sand compaction curves, were derived from linking
two or more with a straight line that has no points falling to its right less compacted side for
formations D, F, H, I, J, K, L and M (Figure 4.3).

25



F H I

J K L

M

Figure 4.3 – Normal compaction curves from the Hillis method for formations D to M

26



4.2 Exhumation Estimations from Compaction Methods

The exhumation magnitudes and associated uncertainties from the Heasler and Hillis
compaction methods are displayed in Figures 4.4 and 4.5, Enclosures 1.4 and 1.5, and Table
4.1. Depths with negative (true) exhumation values were inferred to be overpressured and
removed.

Figure 4.4 – True exhumation estimate for Well 1 using the Heasler method. The mode of the
histogram is the final estimate and uncertainty is defined by the deviation from the mode.

Figure 4.5 – True exhumation estimate for Well 1 using the Hillis method. The mode of the
histogram is the final estimate and uncertainty is defined by the deviation from the mode.

27



Heasler Hillis
True True Post
Well Exhumation Uncertainty Exhumation Uncertainty Exhumational
Name (m) ± (m) (m) ± (m) Burial (m)
Well 1 600 221 560 6 532.3
Well 2 600 226 680 3 643.4
Well 3 550 0 1083.1
Well 5 750 284 860 9 852.3
Well 6 1110 157 770 5 750
Well 8 1400 129 410 1 383.7
Well 9 250 178 570 1 558.7
Well 10 100 440 540 4 530
Well 12 900 243 830 10 797.36
Well 13 600 216 500
Well 14 800 276 890 7 852.3
Table 4.1 - True exhumation estimates for all wells from compaction methods (data for empty
cells are not available due to non-suitability of method)

4.3 Exhumation Estimations from Thermal and Tectonic Methods

The exhumation values calculated from the thermal method are 206.7 m for Well 2 and 30 m for
Well 4. These values are very low compared to estimates from the compaction methods (Table
4.1) and the tectonic method (Table 4.3). They are not valid for reasons outlined in Section
5.1.3.

From the two aforementioned approaches in approximating theoretical subsidence curves from
Section 3.3, the Cochran curve seems to be a more accurate theoretical comparison curve (as
opposed to the McKenzie curve). This was concluded from comparing the (true) exhumation
estimates approximated by comparing water loaded backstripped basement depths with that
estimated by the curves for Well 10 with calculated by the compaction methods. As Table 4.2
shows, the exhumation estimates from the Cochran method shows a much better match with
the ranges predicted by compaction methods.

True Exhumation for Well 10 (m)
Tectonic Compaction
Cochran McKenzie Heasler Hillis
483.9 3330 100 540
Table 4.2 - True exhumation estimates for Well 10 from tectonic and compaction methods

Thus, the Cochran technique was used to calculate exhumation values for the remaining wells
(Table 4.3). This was particularly important for Wells 4 and 11, as both were not suitable for the
compaction method for exhumation analysis.

28



Water
Predicted Post True
Well Stretch loaded Uncertainty
basement Exhumational Exhumation
Name factor basement ± (m)
depth (m) Burial (m) (m)
depth (m)
Well 1 1.85 2250 2100 532 682 0
Well 2 2.4 2890 2600 643 933 0
Well 3 2.5 3000 3500 1083 583 5
Well 4 2 2320 3000 1038 358 115
Well 5 1.6 1890 2000 852 742 10
Well 6 1.2 900 500 750 1150 50
Well 8 1.5 2430 1700 384 1114 740
Well 9 1.8 2220 2400 559 379 10
Well 10 1.6 1900 1946 530 484 0
Well 11 1.7 2100 2565 534 69 40
Well 12 2.5 3000 2700 797 1097 5
Well 13 1.7 2100 1900 500 700 40
Well 14 1.7 2100 2100 852 852 40

Table 4.3 - True exhumation estimates for all wells from the tectonic method

4.4 Final Erosion Values

The exhumation values from the Heasler, Khalid, Hillis and tectonic methods were compiled to
generated erosion values for four cases in Table 4.4 – a low case, a high case, a best case and
a Khalid method case. The final erosion values were picked based on the best methods for
each well section.

Low High Best Method Uncertainty Erosion
Well Name (m) (m) (m) Used ± (m) Khalid (m) Literature
Well 1 379 821 600 Heasler 221 600
Well 2 374 826 600 Heasler 226 -142
Well 3 550 550 550 Heasler 0 529
Well 4 243 473 358 Tectonic 115
Well 5 466 1034 750 Heasler 284 738
Well 6 953 1267 1110 Heasler 157 1110
Well 8 1271 1529 1400 Heasler 129 1377
Well 9 72 428 250 Heasler 178 134
Well 10 536 544 540 Hillis 4 300
Well 11 29 109 69 Tectonic 40
Well 12 657 1143 900 Heasler 243 162
Well 13 384 816 600 Heasler 216 590
Well 14 524 1076 800 Heasler 276 787
Well 15 800
Table 4.4 – Final erosion estimates for all wells for low, high and best cases. The literature
erosion estimates for Wells 10 and 15 were obtained from Ngah (1990).

29



4.5 Basin Models

4.5.1 1D

Maturity-burial histories, and event charts were generated for Wells 1, 2, 5, 8, 9, 10, 11, 12, 13
and 14 (Section 5.4; Enclosures 2.5 to 2.10) for different cases of erosion (Table 4.5). The
erosion values not listed in Table 4.4 was picked based on fitting to VR and SBHT data tried out
for different possible erosion values. The best case erosion estimates were found to fit the
thermal parameters the best (Enclosures 2.2 to 2.4).

Well Erosion Well Erosion Well Erosion Well Erosion
Name (m) Name (m) Name (m) Name (m)
Well 1 379 Well 2 374 Well 5 466 Well 8 1271
Well 5 1034
Well 9 428 Well 11 700 Well 12 1143
Well 13 384 Well 14 524
Well 13 600 Well 14 800
Well 13 816 Well 14 1076
Table 4.5 – Different erosion magnitudes used in 1D basin modeling for all wells.

4.5.2 2D

The hydrocarbon saturations and erosion thickness effects on hydrocarbon migration are shown
in Section 5.4.3.

30



5. DISCUSSION

5.1 Comparison of Methods

The four methods used in this study which are the (Heasler and Hillis) compaction, thermal and
tectonic methods (outlined in Section 3. Methodology), are found to be useful under different
circumstances based on a methodological point of view.

The Heasler method is better suited for sections with high clean shale to clean sand ratios and
vice versa of the Hillis method. The reason for this is because Heasler compaction curves are
more similar to shale compaction trends and Hillis compaction curves to sand compaction
trends (Section 3.2). For a carbonate dominated section, a velocity based compaction approach
used by Japsen (1998) is recommended as porosities vary greatly in carbonates and thus
significant fluctuations in interval transit time may arise due to porosity changes rather than a
past exhumation event. This dilemma is solved in a velocity based approach.

A variation on the Heasler method used by Ngah (1990), where the amount of exhumation
undergone after the formation of an associated unconformity is taken away from total
exhumation (obtained from the Heasler method) to give the amount of erosion.

The tectonic method, in this study, produces exhumation estimates close to that of the most
suitable compaction methods, but the uncertainty for this method is variable as this does not
only come from uncertainty in stretch factor (this study), but also from uncertainties in the
modeling of the theoretical subsidence curve, which has many potential uncertainties due to the
high number of parameters involved in the modeling (Madon and Watts, 1998; Allen and Allen,
2005).

Although a faster technique compared to the aforementioned three, the VR thermal method is
not suitable for sections with no vitrinite reflectance above the unconformity concerned (such as
in this study) and is subject to limitations as outlined in Section 5.1.3 below. The VR data can
also be combined with other organic thermal indicators such as Fluorescence Alteration of
Multiple Macerals (FAMM) and FT data to give the final thermal history.

5.1.1 Uncertainties in the Compaction Methods

As it can be deduced from Table 4.1, the uncertainty range for results from the Heasler method
is two orders of magnitude greater than that of the Hillis method. This is due to the fact that Hillis
normal compaction curves are computed for every formation whereas only one Heasler normal
compaction curve is used for all formations. For Well 1, where clean sands and shales are
distributed more or less equally throughout the stratigraphy, the estimated amounts of
exhumation from Heasler and Hillis methods are close with only 40m of difference. However,
the uncertainty for the Hillis method is much smaller than that of the Heasler method. This
suggests that the accuracy for the two methods does not differ much but the precision of the
Hillis method is greater than that of the Heasler method.

5.1.2 Compaction versus Tectonic Method

In the two adaptations of the compaction method used in this study, the Hillis method proved to
have a substantially smaller range of uncertainty compared to the Heasler method. However,
the more mathematically rigorous Heasler method involves fewer extrapolations compared to
the Hillis method. Despite this, it is still recommended that the Heasler method be used for

31



shale-dominant sections and the Hillis be used for sand-dominant sections (and a velocity
based approach for carbonates) due to the reasons outlined above.

The normal compaction trends for basins where regional exhumation has occurred, for example
the Malay Basin in this study, cannot be established reliably due to the lack of un-exhumed
sections and formations. Interval transit time is also sensitive to porosity, particularly if it is
derived from density logs (Taylor, 2007).

The compaction methods also operate under the assumption that mechanical compaction is the
dominant control on porosity loss through burial, although this might not always be the case
such as in Malay Basin where the low porosities are associated with chemical compaction due
to the high geothermal gradients (Hoesni et al., 2007). Shales, however, are less susceptible to
chemical compaction (which operates through the dissolution and re-precipitation of minerals
and is controlled by thermal processes) compared to sands. Chemical compaction also
operates in the Gulf of Mexico Basin, the Norwegian Shelf and the Baltic Region (Lander and
Walderhaug, 1999).

If the magnitude of post-exhumational burial is equal to the amount of exhumation, then the
effect of exhumation on porosity loss would be neutralized and thus the compaction trend from
such a section would appear to be (falsely) normally compacted (Figure 2.2).

Compaction methods cannot be used for overpressured sections, which are dominant in the
Malay Basin particularly in the basin center (Madon, 2007). Overpressure is also a common
phenomenon for most North Sea reservoirs (Evans et al., 2003) and the Gulf of Mexico basin
(Mello and Karner, 1996). Overpressure is a result of rapid sedimentation or tectonic
compression (which creates uplifted reservoirs).

The tectonic method in this study was based on a linear relationship found between the stretch
factor and basement depths predicted by the theoretical curves (Figure 5.1).

Figure 5.1 – Stretch factors and the associated predicted basement depths from Madon and
Watts (1998)’s subsidence curves

32



This however, may be an oversimplification of the relationship as there seems to be a departure
from this linearity for stretch factors above 1.7.

The version of the tectonic method used in this study estimates exhumation magnitudes from
the difference between water loaded basement depths and basement depths predicted by
theoretical backstripped curves of various locations in the Malay Basin by Madon and Watts
(1998) using a version of the uniform stretching model by Cochran (1983). As evident in Figure
3.6, this model has the two phases of McKenzie’s stretching model: an initial syn-rift subsidence
phase followed by thermal subsidence phase.

Thermal subsidence would begin in the basin center where the geotherms have suffered the
greatest distortion from rifting. The rate of thermal subsidence decreases exponentially with time
and reliance of heat flow stretch factor decreases. Thus the reliance on of heat flow on stretch
factor decreases towards the basin center as thermal subsidence in center started earlier.

This explains the departure from the linear relationship between predicted basement depths and
stretch factors mentioned above. As stretch factors increase towards the basin center (where
thermal subsidence has been longer), the dependence of thermal subsidence on these higher
stretch factors in the Malay Basin is lower.

Uncertainties in stretch factor (0.1) may also cause up to 500 m of uncertainty in the predicted
basement depths.

Other studies (Rowley and White, 1998; Corcoran and Doré, 2005) used different versions of
the (theoretical) uniform stretching model in their tectonic method to estimate exhumation. This
does not imply that one model is better over the other. A stretching model that suits the basin
under study most should be used.

Despite the fact that the tectonic method can be used in overpressure sections and any lithology
as opposed to the compaction method, it can only be applied to basins which follow McKenzie’s
uniform stretching model and shows varying ranges of uncertainty (Table 4.3).

Due to this varying range of uncertainty and the fact that this version of the tectonic method is
being used for the first time, the final erosion values were taken from the compaction methods
instead. However, the tectonic method proved useful in providing erosion values for Wells 4 and
11, where the compaction methods could not be applied.

5.1.3 Erosion Estimates from Vitrinite Reflectance

The thermal method is the least time consuming method out of all the methods. The wells in this
study, however, mostly only have vitrinite reflectance data below the UMU, which negates the
use of the method in Gallagher (2008), except for Well 4. The Well 4 VR profile, however,
shows the discontinuity (due to exhumation) about 200 meters below the measured
unconformity.

The Green et al., (2002) method was used on Well 2 but was invalid for all other wells with
SBHT data as there is a widespread suppression of vitrinite reflectance (deviations of VR profile
towards lower values) in this area, possibly due to the presence of hydrogen–rich vitrinites.

The estimated erosion values from this method are very low and do not correlate well with those
from the other methods (Table 4.4). This is a result from the suppression of vitrinite reflectance
in the area. Other limitations associated with the thermal method include:

33



i) Non-linear palaeo-temperature profiles cannot be used to estimate the magnitude of
exhumation at a given well location (Duddy et al., 1998).

ii) Palaeo-thermal indicators such as VR and FT are dominated by maximum palaeo-
temperatures and do not preserve information on thermal events that occurred prior to the
achievement of peak palaeo-temperatures.

iii) Translation of VR values into absolute palaeo-temperatures can introduce systematic errors
in the estimation of palaeo-geothermal gradients and consequently, the magnitude of
exhumation (Green et al., 2002).

iv) Variations in the chemical composition of vitrinite, between well locations, may lead to invalid
comparison of VR gradients and associated exhumation estimates.

5.14 Discrepancies

Estimations of erosion from the interpreted seismic cross-section in Figure 1.4B shows
consistency with compaction method estimates for Well 9, but inconsistencies with those of
Wells 8 and 13. The erosion value approximated from the seismic section for Well 13 is
significantly higher than the best case estimate by 500 m; and those of Well 8 shows a
difference of -177 m (Enclosure 1.6). The erosion values from the seismic section, however, are
not without uncertainty as the original depositional thicknesses vary.

As shown in Table 4.4, the relative erosion estimates for Wells 8 is very high whereas the
opposite is true for Well 11. The erosion estimate for Well 13 is relatively low considering its
close proximity to Well 8. The erosion estimates for Well 8 and 13 was calculated using the
Heasler compaction method; whereas that of Well 11 was calculated using the tectonic method.

The formation tops for Wells 8 and 13 listed in Figure 3.2 show that there is a lot of missing
strata in these wells. This may have led to low representation of strata in the Heasler
compaction method, which may have skewed erosion estimates for these wells.

As shown in Figure 1.2, inversion (and hence exhumation of eroded section) occurred during
the deposition of formations D to H, and would thus affect these formations the greatest. Well 8
is comprised only of formations D and L, whereas Well 13 of only formations J, K and L. Hence,
any reduction in transit time caused by exhumation can only be measured for formations D and
L for Well 8, and formations J, K and L for Well 13: the exhumation effects on the rest of the
formations are not measured and this gives rise to statistical misrepresentation (Table 5.1).

Well Well Exhumed
Table 5.1 -
8 13 Formations
D Formations present in Wells 8 and 13; versus
E formations affected by exhumation
F
H
I
J J
K K K
L L L
M

34



Well 11, on the other hand, has a near complete set of formations. However, as the tectonic
method was used to calculate the erosion for this well, other factors are needed to explain the
relatively low erosion estimates from this well. As stated in Section 5.1.2, an uncertainty of 0.1 in
stretch factor may cause up to 500m of uncertainty in the theoretically predicted subsidence,
which translates to 500m of uncertainty in exhumation estimates, on top of the uncertainty given
in Table 4.3.

5.2 Erosion Trends

Erosion values between the wells in the study area can be obtained via the creation of
exhumation contour maps controlled by data points with estimated erosion values (such as the
well sections in this study area). The calculated erosion for a well within the study area from
Ngah et. al (1996) was added to the data points to provide better deterministic control over the
contours. Erosion maps based on the calculated exhumation values were computed in two
steps.

Firstly, erosion contour maps were computed using 3DField using minimum curvature, block
kriging, block radial basis function, and linear equation algorithms. The minimum curvature map
was found to be the closest fit to facies changes in the study area.

Hence, the minimum curvature contour map was compared with variations in palaeo-
environment for the E formation (deposited at the time of peak inversion) and inversion axes as
both were thought to have a strong correlation with erosion trends. The contour map, which was
generated based on only erosion values for the well locations, did not correspond well with the
inversion axes (Figure 5.2a) but seem to be influenced by variations in facies (Figure 5.2b),
although this is not a tight correlation. However, the contours are roughly perpendicular with the
inversion axes (Figure 5.2a) which is similar to the relationship between exhumation contours
and inversion axes in the Eromanga basin, Australia (Hillis and Mavromatidis, 2005).

The contour maps for the best, low and high cases of erosion had similar erosion trends and so
the aforementioned comparisons were only done for the best estimates of erosion.

As shown in Figure 5.2b, there are a lot of lateral changes in palaeo-environment in the more
distal southeast part of the study area during the time of Formation E. In subarea X, a distal
floodplain widens outward to the east-southeast where (probable) palaeo-rivers flow west from
the basin margin. This corresponds to an area of high erosion. This is also true for a palaeo-
river further southeast.

Probable palaeo-river locations are marked in Figure 5.2b based on distal floodplain trends. It
becomes more distal south of that which corresponds to a topographic high at time E (see
cross-section in Figure 1.4). The eastern exhumation low in the map is situated away from the
path of the palaeo-rivers and is thus spared from heavy erosion. Erosion decreases towards the
west as the environment goes to more distal swamps (lower energy due to distance from
waves, rivers and tides).

The second step was thus to modify the contour map manually to loosely follow facies changes
in parts where there are less control points (Figure 5.2), to give the final exhumation map.
These steps were done for the best, low and high case estimates of exhumation to produce

35



three exhumation maps for each case (Figure 5.3). As Figure 5.3 shows, the area of high
exhumation in the southeast grows as the exhumation estimates increase from the low to the
best to the high case maps.

N Figure 5.2 –
Exhumation map over

a) Inversion anticlinal
axes (top) indicated
by green lines. Broken
black lines indicate
the AMFZ

b) Palaeo-geography
during peak inversion
in 12.5 Ma (bottom).
Red lines indicate
probable locations of
a) palaeo-rivers
110km Both maps are
modified from Madon
et al., 1999.

Flow
direction

Probable
palaeo- river
locations

b) x
110km
Erosion contour

36



Figure 5.3 –

Erosion maps for a) low, b) best
and c) high cases of erosion

x
Erosion contour

110km
a) Low Case

110km
b) Best Case

110km
c) High Case

37

Investigation of the amount of erosion at the upper Miocene unconformity in the southeastern part of the Malay Basin (2008)

Investigation of the amount of erosion at the upper Miocene unconformity in the southeastern part of the Malay Basin (2008)

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