Microseismic Reservoir Monitoring

Ann-Sophie Boivineau

Geosciences Domain Leader, SIS Paris

aboivineau@slb.com

1

Presentation Outline

• What are microseismic events?

• Applications of microseismic monitoring

• Case studies

• Tools

2

Microseismicity: causes and mechanisms

Confining stress

Pore

PressureShear stress

• Injection

• Production

3 Jupe et al. 2003

Information from microseismic data 1/2

Phase hodogram

Direction of source

Distance to source

P arrival S arrival

Dt

Microseismic event record P and S waves propagating at

different velocities

Particle motion

Location of source

P and S time

difference

+

4

Information from microseismic data 2/2

Source parametersSource radius

Stress drop

Seismic moment

Magnitude

Am

p

Freq

Displacementspectra

Geomechanical model Reservoir properties

or

Moment Tensors

Fracture orientation

Stress fieldPolarity

&

Amplitude

Shear wave SplittingPhase

hodogram

DFN

5

What are its applications?

• Improve the structural knowledge of the reservoir

• Identify active faults thus potential dangerous zones for drilling

• Identify sealed faults, compartments

• Leakage localization during caprock integrity issues

• Fluid Front monitoring

6

Case study #1: EOR, cluster around injector

Jones et al, 20047

Case study #2: Acid injection

Phase 1 Phase 2 Phase 3

Microseismic monitoring during acid

injection allowed to • map the location of an important

permeable fracture

• This information was included into the

fracture network model in the new

static model

Rinck et al, 20098

Case study #3: 2 years monitoring at Karachaganak (2009-2010)

• Carbonate reservoir overlain by deposits of permian evaportites

• Imaging the producing levels difficult with conventional surface seismic methods

• Deployment of microseismic monitoring to better understand the reservoir structure and internal

geometries

Morosini et al, 2012

9

Case study #3: 2 years monitoring at Karachaganak (2009-2011)

• Majority of events located in Permian (light blue)

and Carboniferous reservoir (green-yellow)

• Within carbonate plateform or along its margin

(SE events = slippage of evaporites along the

steep permian carbonates)

• Some groups directly correlated with well

operations (drilling issue SE group)

• Events occur in clusters or along linear features

(geological structures N group in yellow)

modified from Maver et al. 200910

Methodology

• Feasibility study to design the monitoring network

• Acquisition

• Processing of microseismic data to detect and locate

microseismicity, and compute source parameters (stress

drop, source radius, seismic moment, Mag)

• Compute Fault plane solutions to understand the rupture

mechanisms

• Interpretation of space and time distribution of the

microseismic events located, DFN model calibration,

geomechanical study

DFN Model Calibration

Moment Tensor

InversionMicroseismic events

Failure Plane Extraction

Detectability

11

Network design

Given the probability of detecting and locating

microseismic events, the survey design provides

the best configuration for the acquisition array

(proposed well and acquisition array

geometries)

Input: velocity model, noise level, target

Output: detectability map and uncertainty map

12

Acquisition techniques

Microseismic monitoring networks

Surface

• Surface line or patch

• Shallow Grid

Downhole

• Single well (vertical or horizontal)

• Multi-well

Multi-array

1. Surface lines or patch 2. Shallow hole grid 3. Downhole vertical 4. Downhole horizontal

3

2

4

1

13

Detection & location methods of microseismic events

• Probabilistic Coalescence Microseismic mapping (CMM) provides fully-

automated event detection and location (based on Tarantola and Valette’s pdfs

method 1982)o Look up table (LUT) calculated for travel times and polarization on a grid that

encompasses monitoring area

o Each receiver assess the signal to noise ratio (SNR) using a STA/LTA function

o CMM = Objective function based on the Signal to Noise (SNR) functions at

each receiver

• Geiger event relocation, based on arrival time of each phase and

polarization angle of P and Sh waves

• Multiplets identification (improve time picking on identical events)

14

Drew et al 2013

Microseismic data in reservoir context

faults, wells, events for different stages

15

Conclusions

Microseismic monitoring helps• Image geological structures in the reservoir (when conventional surface seismic

methods fail)

• Identify active faults thus potential dangerous zones for drilling

• Identify sealed faults, compartments

• Define HSE strategy for caprock integrity monitoring

• Make operational decisions

Way forward• Take into consideration the time aspect (loading/unloading, geomechanical study)

• Combine microseismic data with of other geophysical measures (InSAR, GPS, etc..)

Thank you

References

Drew J., White R.S., Tilmann F. a,d Tarasewicz J. Coalescence microseismic mapping. Geophysical Journal International, 195, 1773-1785, 2013.

Jones R, Raymer D, Mueller G, Rynja H, Maron K, Hartung M (2004) - Microseismic Monitoring of the Yibal Oilfield, Oman. SEG Expanded abstracts 23, proceedings

of 74th SEG Annual Meeting, Denver, Colorado 2004

Jupe, A.J., Jones, R., Wilson, S.A. & Cowles, J.F. Microseismic monitoring of geomechanical reservoir processes and fracture-dominated fluid flow. Geological

Society, London, Special Publications, v. 209; p. 77-86, 2003

Maver, K. G., Boivineau, A.-S., Rinck, U., Barzaghi, L. and Ferulano, F. Real time and continuous reservoir monitoring using microseismicity recorded in a live well,

First Break, vol 27, pp 25-29, July 2009.

Morosini, M., T. Daley, M. Eales, A.-S. Boivineau, C. Nicou and A. Jupe. Continuous deep microseismic monitoring of the Karachaganak field, Kazakhstan:

inteegrating reservoir geoscience, drilling and engineering, Petroleum Geoscience, vol 18, pp279-287, August 2012.

Rinck, U.,Maver, K. G. and Boivineau, A.-S., Downhole noise analysis and control for microseismic dat acquisition in a live well, 11th International Confress of the

Brazilian Geophysical Society, Salvador, Brazil, August 24-28 2009.

Tarantola, A. & Valette, B. Inverse problems = quest for information,

J. Geophys., 50, 150–170. 1982.