Microseismic Reservoir Monitoring

Transcription

1 Microseismic Reservoir Monitoring Ann-Sophie Boivineau Geosciences Domain Leader, SIS Paris 1 aboivineau@slb.com

2 Presentation Outline What are microseismic events? Applications of microseismic monitoring Case studies Tools 2

3 Microseismicity: causes and mechanisms Injection Pore Pressure Confining stress Shear stress Production 3 Jupe et al. 2003

4 Information from microseismic data 1/2 Microseismic event record P and S waves propagating at different velocities Dt P and S time difference Distance to source P arrival S arrival Particle motion + Direction of source Phase hodogram 4 Location of source

5 Amp Information from microseismic data 2/2 Freq Displacement spectra Phase hodogram Source parameters Source radius Stress drop Seismic moment Magnitude Shear wave Splitting 5 or Polarity & Amplitude Moment Tensors Fracture orientation Stress field DFN Geomechanical model Reservoir properties

6 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

7 Case study #1: EOR, cluster around injector 7 Jones et al, 2004

8 Case study #2: Acid injection 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 8 Phase 1 Phase 2 Phase 3 Rinck et al, 2009

9 Case study #3: 2 years monitoring at Karachaganak ( ) 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,

10 Case study #3: 2 years monitoring at Karachaganak ( ) 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) 10 modified from Maver et al. 2009

11 Methodology Detectability 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 Microseismic events DFN Model Calibration Moment Tensor Inversion Failure Plane Extraction 11

12 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

13 Acquisition techniques Microseismic monitoring networks Surface Surface line or patch Shallow Grid Downhole Single well (vertical or horizontal) Multi-well Multi-array Surface lines or patch 2. Shallow hole grid 3. Downhole vertical 4. Downhole horizontal

14 Detection & location methods of microseismic events Probabilistic Coalescence Microseismic mapping (CMM) provides fullyautomated 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 Drew et al 2013 Multiplets identification (improve time picking on identical events) 14

15 15 Microseismic data in reservoir context faults, wells, events for different stages

16 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..)

17 Thank you

18 References Drew J., White R.S., Tilmann F. a,d Tarasewicz J. Coalescence microseismic mapping. Geophysical Journal International, 195, , 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 , 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 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, pp , August Rinck, U.,Maver, K. G. and Boivineau, A.-S., Downhole noise analysis and control for microseismic dat acquisition in a live well, 11 th International Confress of the Brazilian Geophysical Society, Salvador, Brazil, August Tarantola, A. & Valette, B. Inverse problems = quest for information, J. Geophys., 50,