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T.C. Coburn

Publications and source records attributed to T.C. Coburn.

2 recordsLinked to original sources

Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells

The application of horizontal and hydraulically fractured wells for producing oil from low permeability formations has changed the face of the North American oil industry. One feature of the production profile of many such wells is a transition from transient linear oil flow to boundary-dominated flow. The identification of the time of this transition is important for the calibration of models that forecast the well’s future production and the expected ultimate recovery. It is preferable that such models generally use data from the boundary-dominated flow regime for parameter calibration. Accurate well production forecasts are needed for operational decisions, long-term planning, commercial transactions, regulatory proceedings, and asset valuation. Petroleum engineers frequently make the call on the transition point based on subjective visual interpretations of log–log plots for individual wells. This is time-consuming and is generally not repeatable by other analysts. This note evaluates statistical approaches that can serve as alternatives to the subjective visual interpretations. Specifically, the predictive performance of production models calibrated with boundary-dominated data based on transition dates calculated with constrained nonlinear least squares and Bayesian regressions was very close to that obtained using the visual method, suggesting that statistical approaches may indeed be constructed to replace less objective visual approaches without loss of accuracy.

Natural Resources Research

Evaluation of procedures for prediction of unconventional gas in the presence of geologic trends

This study extends the application of local spatial nonparametric prediction models to the estimation of recoverable gas volumes in continuous-type gas plays to regimes where there is a single geologic trend. A transformation is presented, originally proposed by Tomczak, that offsets the distortions caused by the trend. This article reports on numerical experiments that compare predictive and classification performance of the local nonparametric prediction models based on the transformation with models based on Euclidean distance. The transformation offers improvement in average root mean square error when the trend is not severely misspecified. Because of the local nature of the models, even those based on Euclidean distance in the presence of trends are reasonably robust. The tests based on other model performance metrics such as prediction error associated with the high-grade tracts and the ability of the models to identify sites with the largest gas volumes also demonstrate the robustness of both local modeling approaches. ?? International Association for Mathematical Geology 2009.

Natural Resources Research