ann-sophie boivineau geosciences domain leader, sis paris · 2019-04-15 · hodogram dfn 5. what...
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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 #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
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..)
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.
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