http://www.geomage.com Predict fracture swarms and small offset faults using conventional seismic data

1. MultiFocusing Diffraction Imaging
(MFDI)

2. Outline
• Introduction and theory
• Numerical model
• Case studies
– Case 1 – Mediterranean
– Case 2 – integrated study 1
– Case 3 – integrated study 2

3. Theory

4. Conventional NMO
X – source
V 1ρ 1
R – receiver
V 2ρ 2
offset offset
time
Before NMO correction After NMO correction

5. 2D MultiFocusing – 3 parameters
CRE radius & CEE radius and emergence angle

6. Diffraction - definition
obstacle
wavefront

7. Why diffraction?
• strong need for small-scale natural fracture and
fault detection
• seismic wavefront contains certain fracture
information, difficult to extract
• diffraction, key to higher resolution

8. MultiFocusing diffraction imaging (MFDI)
• MF imaging stacks large number of traces and
increases S/N ratio
• weak seismic events are enhanced
• diffraction energy contains important information
but is weak and sensitive to noise
• MF diffraction imaging methodology increases
diffraction S/N ratio

9. Diffraction stacking – a special case of
MultiFocusing stacking
Diffraction moveout coincides with MultiFocusing moveout when the
reflection interface shrinks to a point, i.e., when RCRE = RCEE.

10. Outline
• Introduction and theory
• Numerical model
• Case studies
– Case 1 – Mediterranean
– Case 2 – integrated study 1
– Case 3 – integrated study 2

11. Numerical diffraction model
fractures
20 km

12. Fracture density increases along model
length
Size of fracture: 1 x 0.3 meter
fractures
depth (m)
distance (m)

13. 2D-model MultiFocusing stack

14. 2D-model MultiFocusing post-stack
migration

15. 2D-model MultiFocusing diffraction
stack

16. 2D-model MultiFocusing
diffraction post-stack migration

17. Outline
• Introduction and theory
• Numerical model
• Case studies
– Case 1 – Mediterranean
– Case 2 – integrated study 1
– Case 3 – integrated study 2

18. Case study 1: geology

19. Geomage MultiFocusing – structure stack

20. Geomage MultiFocusing – diffraction stack

21. MultiFocusing – migrated diffraction stack
evaporites
diffraction values in color on migrated MF stack

22. Geomage MultiFocusing – diffraction stack

23. MultiFocusing diffraction velocities
smoothed velocity corrected velocity
from MF processing from MF diffractions
m/s

24. Outline
• Introduction and theory
• Numerical model
• Case studies
– Case 1 – Mediterranean
– Case 2 – integrated study 1
– Case 3 – integrated study 2

25. Integrated diffraction case study 1
Goal – predict fractured zones within unconventional
reservoir onshore Europe
formation: oil-shale
average thickness: 40 m
well data:
– log data of six wells
with old and poor logs
– incomplete well tests
– key information on two
wells kept back as blind
test

26. Integrated diffraction case study 1
formation: oil-shale
average thickness: 40 m
seismic data
– diffraction
– amplitudes
– attributes

27. Project scope
– seismic structural interpretation, seismic
attribute analysis
– MultiFocusing diffraction imaging
– petrophysical analysis and well log
interpretation
– clusters and statistical analysis
– geological review and conclusion

28. Seismic PSTM amplitudes
Well A Well B Well C

29. Horizon maps
time map depth map
? ?
? ?

30. Temperature map at reservoir
temperature (degrees C)
135
Well B 130
125
130
120
115
Well C
110
100
3 105
100
Well A 139 95
90
85
80
75 70
70

31. Pressure map at reservoir
460
460
Well B 440
pressure (PSI)
420
400
380
360
Well C
3
340
340
320
Well A
300
280
260
240
220
180
200
180

32. Well-to-seismic ties
reservoir
reservoir
Max.Corr = 0.82 Max.Corr = 0.79

33. PSTM in background, diffraction image in
color
Well A Well B
increasing evidence of
fracturing and facies change in
areas of uplift and compression

34. PSTM in background, diffraction image in
color
increasing evidence of
fracturing and facies change in
areas of uplift and compression

35. of fractures
additional
Petrophysical results and diffraction
meability
Trace of Diffraction
p_ nk image
trace along well paths
US-7
APS Lithology index
Resistivity from tool
VSH with big and short Parametr of fractures
radius of investigation Truth Formation and additional
NGK60 PZ resistivity permeability
Trace of Diffraction
GR BK Flush zone resistivity Kp_nk image
Q 16
н=
3
м/сут
Кровля баж.
свиты
Сухо
Кровля абалак.
свиты

36. Diffraction amplitudes and well results
diffraction image horizon map production rate vs diffraction
amplitude
B
C
A production rate
diffraction amplitude
correlation coefficient = 0.7

37. Diffraction amplitudes and well results
diffraction image horizon map in situ porosity vs diffraction
amplitude
B 80
y = 33.229ln(x) + 26.969
R² = 0.8827
70
y = 22.734ln(x) + 21.653
in situ porosity (%)
60 R² = 0.8434
B
C 50 y = 32.477ln(x) + 30.932
A R² = 0.8434
40
Qsr
30 C
A Q2
20
Q3
m
u
o
n
L
v
a
e
r
l
i
10
0
0 1 2 3 4
Diffraction image, у.е
diffraction amplitude
average correlation coefficient: 0.85

38. Attribute horizon maps around various well
locations composite map: first derivative of
envelope, diffraction amplitude,
temperature, pressure
calculated in situ porosity map
BB B
C C C
A A
A

39. Outline
• Introduction and theory
• Numerical model
• Case studies
– Case 1 – Mediterranean
– Case 2 – integrated study 1
– Case 3 – integrated study 2

40. Integrated diffraction case study 2
Goal – predict fractured zones within unconventional
reservoir, onshore Americas
100041300222W400
formation: oil shale
Resistivity and Properties Porosities Param ether of fractures Paramether of fractures Param ether of fractures
n imp
D of flush zone DEN KPnk_gk KPfrac2 DIFR2DDIV100 KPfrac9 0 10 7000 21000
Dzona2 2300 2900 0 0.2 0 0.001 0 0.014 0 0.001 LIT PE
5 10 DT KPfrac1 KPfrac4 KPfrac11 1 5 0 10
MD,м
RES_DEP 150 300 0 0.001 0 0.001 0 0.001 GR
average thickness: 11 m
0 2000 GR KPfrac6 KPfrac10 0 500
RES_MED 0 500 0 0.0001 0 0.001 DEN
0 2000 den_correct SEISMIC 2300 2900
RES_SLW 2300 2900 -8000 8000
0 2000
2480
well data:
2500
– six wells were within the
2520
2540
survey limits 2560
– only five could be used 2580
– old wells with
2600
2620
incomplete information 2640
D flash zone

41. Integrated diffraction case study 2
Goal – predict fractured zones within unconventional
reservoir, onshore Americas
formation: oil shale
average thickness: 11 m
seismic data
– amplitudes
– attributes
– diffraction amplitudes
– diffraction velocities

42. Project scope
– diffraction imaging
– seismic attribute analysis
– petrophysical analysis and well log
interpretation
– clusters and statistical analysis
– geological review and conclusion

43. Seismic arbitrary PSTM amplitude section
Well A Well B Well C

44. Time map at main target interval

45. Seismic-to-well tie
Well D

46. PSTM amplitudes around target horizon
main horizon minus 30 main horizon minus 12
ms ms
F F
C
C
B
B
A
A

47. Petrophysical analysis
calculated fracturing
100052700124W400
Resistivity and D of flush zone Porosity, Litology and clayness Paramether of fractures Traces of seismic attributes, Impedance, Vrelationship (logs)
Dzona2 VSH KPfrac
5 16 0 1 0 1E-5 SEISMIC
MD,м
RES_DEP KPnk_gk DIFR -9000 9000
0 1950 0 0.1 0 0.01 im p
RES_MED 10000 25000
0 1950 dV
0.9 1
dVs_p
0 1
2688
2700
depth (m)
2712
2724
2736
2748
2760
2772
2784

48. Cross-plot, calculated in situ porosity
and diffraction
in situ porosity (%)
correlation coefficient: 0.9
diffraction amplitude

49. Diffraction interpretation
diffraction amplitude
main horizon -12 ms secondary target

50. Integrating digital elevation model (DEM)
anomaly not caused by surface condition
DEM
diffraction amplitude

51. Integrating digital elevation model (DEM)
anomaly possibly caused by surface condition.
DEM
diffraction amplitude

52. Summary
• three case studies
• petrophysical analysis – natural fracturing,
in situ porosity
• MF diffraction amplitude - calibrate to wells
• calculate seismic attributes
• all data types integrated

53. Conclusions
• correlation between diffraction amplitudes and
natural fractures
• prediction of fracture swarms in tight shales
• integrating other data types enhances fracture-
prediction accuracy