Reservoir: Integration of Shale Gas Production Data and Microseismic for Fracture and Reservoir Properties

Speaker Michael J. King
Dr. Michael J. King is Professor and holder of the Foundation CMG Chair in Robust Reduced Complexity Modeling and the LeSuer Chair in Reservoir Management in the Department of Petroleum Engineering at Texas A&M University. He is the recipient of the 2011 SPE Reservoir Description and Dynamics Award, has served ...

Dr. Michael J. King is Professor and holder of the Foundation CMG Chair in Robust Reduced Complexity Modeling and the LeSuer Chair in Reservoir Management in the Department of Petroleum Engineering at Texas A&M University. He is the recipient of the 2011 SPE Reservoir Description and Dynamics Award, has served as a Distinguished Lecturer for the SPE and is the co-author of the SPE textbook on Streamline Simulation: Theory and Practice. He joined A&M in 2009, after enjoying 27 years with BP America, both in the U.S. and overseas. His original training was in Physics and Mathematics, with a PhD from Syracuse University in 1980.

Full Description

We present a novel approach to calculate drainage volume and well performance in shale gas reservoirs using a Fast Marching Method (FMM) combined with a geometric pressure approximation. Our approach can fully account for complex fracture network geometries associated with multistage hydraulic fractures and their impact on the well pressure and rates.

 The major advantages of our proposed approach are its simplicity, intuitive appeal and computational efficiency. For example, we can compute and visualize the time evolution of the well drainage volume for multimillion cell geologic models in seconds without resorting to reservoir simulation. A geometric approximation of the drainage volume is then used to compute the well rates and the reservoir pressure.

 The speed and versatility of our proposed approach makes it ideally suited for parameter estimation via inverse modeling of shale gas performance data. We utilize experimental design to perform the sensitivity analysis to identify the most significant parameters and a genetic algorithm to calibrate the relevant fracture and matrix parameters in shale gas reservoirs by history matching of production data. In addition to the production data, microseismic information is utilized to help us constrain the fracture extent and orientation and to estimate the stimulated reservoir volume (SRV). The proposed approach is applied to a fractured shale gas well. The results clearly show reduced uncertainty in the estimated fracture parameters and SRV, leading to improved forecasting and reserve estimation. (This presentation is an expanded version of SPE161357)

When?

Thu, Mar. 28, 2013
11:30 a.m. - 1 p.m. America/Chicago

How Much?

A $5 donation for the SPE-GCS Scholarship Fund has automatically been added to the registration fee. Use OptOut in the Discount Code field if you do not wish to donate at this time.
Event has ended

Where?

Courtyard on St James
1885 Saint James Pl
Houston, Texas 77056
USA

Refund Policy: You must notify the SPE-GCS office of your intent to cancel at least 24 hours prior to the event date to receive a refund. For all refund inquiries, email spe-gcs@spe.org. View our Terms & Conditions for more information.