MultiFocusing Diffraction Imaging (MFDI)

• Introduction and theory

• Numerical model

• Case studies– Case 1 – Mediterranean – Case 2 – integrated study 1– Case 3 – integrated study 2

Outline

Theory

Conventional NMO

Before NMO correction After NMO correction

offset offset

tim

e

V11

V22

X – source R – receiver

CRE radius & CEE radius and emergence angle

2D MultiFocusing – 3 parameters

wavefront

obstacle

Diffraction - definition

• strong need for small-scale natural fracture and fault detection

• seismic wavefront contains certain fracture information, difficult to extract

• diffraction, key to higher resolution

Why diffraction?

• 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

MultiFocusing diffraction imaging (MFDI)

Diffraction moveout coincides with MultiFocusing moveout when the reflection interface shrinks to a point, i.e., when RCRE = RCEE.

Diffraction stacking – a special case of MultiFocusing stacking

• Introduction and theory• Numerical model• Case studies

– Case 1 – Mediterranean – Case 2 – integrated study 1– Case 3 – integrated study 2

Outline

fractures

20 km

Numerical diffraction model

Size of fracture: 1 x 0.3 meter

Fracture density increases along model length

fractures

dep

th (

m)

distance (m)

2D-model MultiFocusing stack

2D-model MultiFocusing post-stack migration

2D-model MultiFocusing diffraction stack

2D-model MultiFocusing diffraction post-stack migration

• Introduction and theory• Numerical model• Case studies

– Case 1 – Mediterranean – Case 2 – integrated study 1– Case 3 – integrated study 2

Outline

Case study 1: geology

Geomage MultiFocusing – structure stack

Geomage MultiFocusing – diffraction stack

MultiFocusing – migrated diffraction stack

diffraction values in color on migrated MF stack

evaporites

Geomage MultiFocusing – diffraction stack

MultiFocusing diffraction velocities

smoothed velocity from MF processing

corrected velocity from MF diffractions

m/s

• Introduction and theory• Numerical model• Case studies

– Case 1 – Mediterranean – Case 2 – integrated study 1– Case 3 – integrated study 2

Outline

Integrated diffraction case study 1

Goal – predict fractured zones within unconventional reservoir onshore Europe

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

formation: oil-shaleaverage thickness: 40 m

Integrated diffraction case study 1

formation: oil-shaleaverage thickness: 40 m

seismic data– diffraction– amplitudes– attributes

– seismic structural interpretation, seismic attribute analysis

– MultiFocusing diffraction imaging– petrophysical analysis and well log

interpretation – clusters and statistical analysis– geological review and conclusion

Project scope

Seismic PSTM amplitudes

Well A Well B Well C

time map depth map

?

?

?

?

Horizon maps

70

75

80

85

90

95

100

105

110

115

120

125

130

135

139

3

Well A

Well B

Well C

Temperature map at reservoir

tem

pe

ratu

re (

de

gre

es

C)

130

100

70

180

200

220

240

260

280

300

320

340

360

380

400

420

440

460

3

Well A

Well B

Well C

Pressure map at reservoir

460

340

180

pre

ssu

re (

PS

I)

Well-to-seismic ties

Max.Corr = 0.79Max.Corr = 0.82

reservoir

reservoir

PSTM in background, diffraction image in color

Well A

increasing evidence of fracturing and facies change in areas of uplift and compression

Well B

PSTM in background, diffraction image in color

increasing evidence of fracturing and facies change in areas of uplift and compression

Petrophysical results and diffraction trace along well paths

US-14

US-6

US-7

Q 2.1н=1м/сут3

Q 16н=м/сут3

Сухо

Кровля абалак.свиты

Кровля баж.свиты

Parametr of fractures and additional permeability

Trace of Diffraction imageК _p nk

К _p nk

Kp_nk

VSH

VSH

VSH

Trace of Diffraction image

Trace of Diffraction image

Parametr of fractures and additional permeabilityParametr of fractures

and additional permeability

Lithology index

Lithology index

Lithology index

Truth Formation resistivity

Resistivity from tool with big and short

radius of investigation

Resistivity from tool with big and short

radius of investigationResistivity from tool with big and short

radius of investigation

Flush zone resistivity

Flush zone resistivity

Truth Formation resistivity

Truth Formation resistivity

Flush zone resistivity

GR

NGK60GR

NGK60

GR

NGK60

APS

APS

APS

PZ

BK

PZ

BKPZ

BK

Diffraction amplitudes and well results

diffraction image horizon map production rate vs diffraction amplitude

B

C

A

diffraction amplitude

pro

du

ctio

n r

ate

correlation coefficient = 0.7

in situ porosity vs diffraction amplitude

y = 32.477ln(x) + 30.932R² = 0.8434

y = 33.229ln(x) + 26.969R² = 0.8827

y = 22.734ln(x) + 21.653R² = 0.8434

0

10

20

30

40

50

60

70

80

0 1 2 3 4

Lin

ear

volu

me

Diffraction image, у.е

Qsr

Q2

Q3

B

A

C

B

C

A

diffraction image horizon map

in s

itu

po

rosi

ty (

%)

diffraction amplitude

average correlation coefficient: 0.85

Diffraction amplitudes and well results

Attribute horizon maps around various well locations

composite map: first derivative of envelope, diffraction amplitude, temperature, pressure

B

A

C

B

C

A

calculated in situ porosity map

B

C

A

• Introduction and theory• Numerical model• Case studies

– Case 1 – Mediterranean – Case 2 – integrated study 1– Case 3 – integrated study 2

Outline

Integrated diffraction case study 2

Goal – predict fractured zones within unconventional reservoir, onshore Americas

well data:– six wells were within the

survey limits – only five could be used– old wells with

incomplete information

formation: oil shaleaverage thickness: 11 m

100041300222W400

MD

,м

Resistivity andD of flush zone

5 10

Dzona2

0 2000

RES_DEP

0 2000

RES_MED

0 2000

RES_SLW

Properties

2300 2900

DEN

150 300

DT

0 500

GR

2300 2900

den_correct

Porosities

0 0.2

KPnk_gk

Paramether of fractures

0 0.001

KPfrac2

0 0.001

KPfrac1

Paramether of fractures

0 0.014

DIFR2DDIV100

0 0.001

KPfrac4

0 0.0001

KPfrac6

-8000 8000

SEISMIC

Paramether of fractures

0 0.001

KPfrac9

0 0.001

KPfrac11

0 0.001

KPfrac10

0 10

n

1 5

LIT

7000 21000

imp

0 10

PE

0 500

GR

2300 2900

DEN

2480

2500

2520

2540

2560

2580

2600

2620

2640

D flash zone

seismic data– amplitudes– attributes– diffraction amplitudes– diffraction velocities

formation: oil shaleaverage thickness: 11 m

Integrated diffraction case study 2

Goal – predict fractured zones within unconventional reservoir, onshore Americas

– diffraction imaging– seismic attribute analysis– petrophysical analysis and well log

interpretation– clusters and statistical analysis– geological review and conclusion

Project scope

Seismic arbitrary PSTM amplitude section

Well A Well B Well C

Time map at main target interval

Seismic-to-well tieWell D

PSTM amplitudes around target horizon

main horizon minus 30 ms

main horizon minus 12 ms

B

C

A

F

C

A

F

B

100052700124W400

MD

,м

Resistivity and D of flush zone

5 16

Dzona2

0 1950

RES_DEP

0 1950

RES_MED

Porosity, Litology and clayness

0 1

VSH

0 0.1

KPnk_gk

Paramether of fractures

0 1E-5

KPfrac

0 0.01

DIFR

Traces of seismic attributes, Impedance, Vrelationship (logs)

-9000 9000

SEISMIC

10000 25000

imp

0.9 1

dV

0 1

dVs_p

2688

2700

2712

2724

2736

2748

2760

2772

2784

D flash zone

Petrophysical analysis

calculated fracturing

de

pth

(m

)

Cross-plot, calculated in situ porosity and diffraction

in s

itu

po

rosi

ty (

%)

diffraction amplitude

correlation coefficient: 0.9

Diffraction interpretation

diffraction amplitude

main horizon -12 ms secondary target

Integrating digital elevation model (DEM)anomaly not caused by surface condition

DEM

diffraction amplitude

anomaly possibly caused by surface condition.

Integrating digital elevation model (DEM)

DEM

diffraction amplitude

Summary

• three case studies

• petrophysical analysis – natural fracturing, in situ porosity

• MF diffraction amplitude - calibrate to wells

• calculate seismic attributes

• all data types integrated

Conclusions

• correlation between diffraction amplitudes and natural fractures

• prediction of fracture swarms in tight shales

• integrating other data types enhances fracture-prediction accuracy