Stochastic simulation of fracture strikes using seismic anisotropy induced velocity anomalies
Samik Sil 1 2 4 Sanjay Srinivasan 31 University of Texas at Austin, Institute for Geophysics, J.J. Pickle Research Campus, Bldg. 196, 10100 Burnet Road (R2200), Austin, TX 78758-4445, USA.
2 Present address: Conoco Phillips, PO BOX 2197, Houston, TX 77252-2197, USA.
3 Department of Petroleum and Geosystems Engineering, University of Texas at Austin, 1 University Station C0300, Austin, TX 78712, USA.
4 Corresponding author. Email: samiksil@gmail.com
Exploration Geophysics 40(3) 257-264 https://doi.org/10.1071/EG08129
Submitted: 30 April 2009 Published: 21 September 2009
Abstract
Availability of a fracture map of a producing reservoir aids in increasing productivity. Generally, accurate information related to fracture orientation is only available at a few sparse well log locations. However, fractures introduce velocity anomalies in seismic data by making the medium azimuthally anisotropic. When multi-azimuth data is available then it is possible to map the fracture attributes in the entire reservoir zone by analysing the anisotropy induced velocity anomalies in the seismic data. In the absence of 3D data, seismic anisotropy induced velocity anomaly from 2D data (as fracture strikes are not constant and data contains multi-azimuthal effect even when it is 2D) can still be used as a secondary source of information for the purpose of fracture strike simulation. To validate the above hypothesis, fracture strike information in a reservoir from the Mexican part of the Gulf of Mexico is derived using Markov-Bayes stochastic simulation. In this simulation process, accurate well log derived fracture information is used as hard or primary data and seismic velocity anomaly/uncertainty based fracture information is used as soft or secondary data. The Markov-Bayes Stochastic simulation provides multiple realisations of the fracture patterns and thus helps to estimate the uncertainty associated with the fracture strikes of the reservoir. Accuracy of the simulation process is also estimated and the simulation result is compared with simple and ordinary kriging methods of fracture strike simulation.
Key words: fracture, geostatistics, Markov-Bayes, seismic anisotropy, stochastic simulation.
Acknowledgments
We are thankful to the editor Lindsay Thomas and Vinay Vaidya of Exploration Geophysics for their help. We are also thankful to Dr Ravi P. Srivastava and Dr Abhijit Gangopadhya for their constructive criticism and suggestions which made this manuscript better. This work is a part of the reservoir model uncertainty estimation project conducted by the petroleum engineering department of UT Austin with funding received from G&W Systems.
Angerer, E., Lanfranchi, P., and Rogers, S. F., 2003, Fractured reservoir modeling from seismic to simulator, A reality? Leading Edge 22, 684–689.
| Crossref | GoogleScholarGoogle Scholar |
Dix, C. H., 1955, Seismic velocities from surface measurements: Geophysics 20, 68–86.
| Crossref | GoogleScholarGoogle Scholar |
Grechka, V., and Tsvankin, I., 1999, 3-D moveout velocity analysis and parameter estimation for orthorhombic media: Geophysics 64, 820–837.
| Crossref | GoogleScholarGoogle Scholar |
Tran, N., Chen, Z., and Rahman, S., 2006, Integrated conditional global optimisation for discrete fracture network modelling: Computers & Geosciences 32, 17–27.
| Crossref | GoogleScholarGoogle Scholar |