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AAPG Bulletin, V.
A novel technique for modeling fracture intensity: A case study from the Pinedale anticline in Wyoming Patrick M. Wong1
1Veritas Exploration Services, A Division of Veritas Geophysical Corporation, 10300 Town Park Drive, Houston, Texas; email: [email protected]
Patrick Wong holds a B.E. degree and a Ph.D. in petroleum engineering from the University of New South Wales (UNSW), Australia. He is currently a project reservoir engineer at Veritas Exploration Services, Houston. Prior to this, he was a senior lecturer of petroleum engineering at UNSW. He has published more than 90 articles on new approaches in reservoir modeling and characterization.Patrick Wong holds a B.E. degree and a Ph.D. in petroleum engineering from the University of New South Wales (UNSW), Australia. He is currently a project reservoir engineer at Veritas Exploration Services, Houston. Prior to this, he was a senior lecturer of petroleum engineering at UNSW. He has published more than 90 articles on new approaches in reservoir modeling and characterization.
The author thanks Hussein Almuallim, Sean Boerner, and Dave Gray for reviewing the first draft of the paper and Veritas Geophysical for permission to publish the results of the case study. Valuable comments from the AAPG editor John Lorenz and three anonymous reviewers are also acknowledged.
Fracture intensity indicators from well data are highly uncertain when applied or extrapolated to the whole field. Statistical techniques offer some useful tools for dealing with such problems in reservoir modeling. The recent research and development of effort focuses strongly on the development of hybrid techniques that aim at overcoming the inherent assumptions and limitations of individual techniques and taking into consideration uncertain data for estimating error bars (or confidence bounds) on the calculated outputs. This paper presents a recently developed hybrid technique based on soft computing methods and shows how this technique can be used to improve the workflow of fracture characterization and sweet-spots identification. It uses a set of rock matrix properties and a fracture-related seismic attribute to simulate a three-dimensional fracture intensity model at the Pinedale anticline in Wyoming. The estimated fracture intensity results agree very well with the data at four virtual wells. It also shows that use of the fracture intensity estimations, together with their error bars, is a valuable tool for the identification of potential sweet spots with reduced risks.
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