9. Carbonate heterolithic classification/9
• For resistivity images:
– Conductive (dark image) =/= Open?
– Resistive (light) =/= Closed?
• For Acoustic Images
– low amplitude (dark) =/= Open?
– high amplitude (light) =/= Closed?
• Core calibration can be used to confirm
– Image logs can only provide an interpretive
insight only
• Only dynamic data provide true insight into
fracture “producibility”
Open versus closed fractures
12. Carbonate heterolithic classification/12
BIU 1
BIU 3A
BIU 2
BIU 3B
Formation
Test
Data
(psi)
110.3
26.2
26.2
25.5
10.4
11.8
9.5
12.8
8.9
8.6
7.9
BIU 3B BIU 2 BIU 1
Bedding contact
WSW ENE
MINOR
FAULT B
MINOR
FAULT A
MAJOR
FAULT A
BIU 3A
Fault compartmentalisation
13. Carbonate heterolithic classification/13
• Well and fracture orientation
• Fracture density
• Core density calibration
• Borehole corrected
fracture density
• Fracture spacing
• Fracture length?
• 3D modelling
Schematic path
dow
n boreho
le
(69* / 210*)
Schematic path
down bo
reho
le
(69* / 210*)
Mesozoic carbonate
Oil staining
OBLIQUE-SLIP
Fracture distribution
14. Carbonate heterolithic classification/14
• Increased compartmentalisation
– Permeability barriers
• Increased communication
– Permeability conduits
• Overall objective - producibility
– Fracture model inputs
– Fault seal predictions
– Production enhancement
– Completion strategy
– Selection of perforation intervals
GO
Fracture characterisation
15. Carbonate heterolithic classification/15
• Image facies assigned on basis of image
character, open hole log response
• Image response is related to electrical or
acoustic properties, responds to rock
texture, fluid saturation and mineralogy
• Not possible to distinguish all core
lithofacies
• Calibration with core allows a meaningful
geological interpretation of image logs
Image facies
24. Carbonate heterolithic classification/24
Image facies show
an overall
coarsening/ shoaling-
upward trend with
increasing stacking
pattern in upper part
of reservoir
Stacked
fining-upward
grain/pack/
wackestone
units
Mostly trendless
succession of
mudstone/
wackestones
Interpretation
Coarse, vuggy rudist
float to rudstones
Image facies prediction in uncored wells
30. Carbonate heterolithic classification/30
15
20
Ft
Elongate conductive patches
represent secondary mouldic
porosity after bioclasts filled
by conductive drilling mud.
Conductive
(open?) fracture
Micro-resistivity
Mouldic and vuggy porosity
31. Carbonate heterolithic classification/31
Vuggy carbonates seen in both acoustic and resistivity images
Image analysis can be used to threshold the image
and determine the % vuggy macroporosity and
degree of interconnectivity
Acoustic Micro-resistivity
Vuggy porosity
34. Carbonate heterolithic classification/34
A RRT has a unique reservoir quality but not
necessarily lithofacies.
• Typically established in cored wells on basis of thin
section and SCAL data.
• Extrapolation into uncored wells using openhole logs
and used to predict permeability.
– fine scale permeability heterogeneity below resolution of
standard openhole logs.
– subtle changes in pore system can result in similar
porosities but permeability can vary by several orders of
magnitude.
• High resolution image logs used for Image Rock
Type (IRT) identification and permeability prediction.
Reservoir rock typing
35. Carbonate heterolithic classification/35
Conductive, high K vuggy
skeletal grainstones
at base of units
Resistive, low K
wackestones at top of
units
Stacked small-
scale fining-
upward units,
with high K
grainstones at
base grading up
into low K
wackestones
Image facies
36. Carbonate heterolithic classification/36
Calculate K statistics and
define K rank
Organise core poro-perm data by image
facies (cross-plots)
Group image facies into K classes:
“image rock types”
Assign image image rock types using porosity
from openhole log data as guide to ‘background’ rock type.
Assign K rank and value along-
side image rock types interpretation
QC predicted K against
measured core K
RRT/ permeability prediction workflow
42. Carbonate heterolithic classification/42
Conclusions
• Borehole image logs provide high resolution, oriented
data sets
– Provide key information on nature, orientation and scale of
fracture and fault systems, and compartmentalisation
– Provide information on texture, lithofacies and reservoir rock
types.
– Porosity and permeability distribution
– Identification of small-scale heterogeneity below resolution of
standard openhole logs
• Make more effective use of uncored wells to build,
constrain & validate 3D reservoir model realisations
