Reservoir: Challenges in Unconventional Reservoir Forecasting

Speaker Shah Kabir
Shah Kabir is a global reservoir engineering advisor at Hess Corporation in Houston. His experience spans more than 30 years in the areas of transient-pressure testing, fluid- and heat-flow modeling in wellbores, and reservoir engineering. Besides coauthoring more than 125 papers, Kabir coauthored the 2002 SPE textbook Fluid Flow and ...

Shah Kabir is a global reservoir engineering advisor at Hess Corporation in Houston. His experience spans more than 30 years in the areas of transient-pressure testing, fluid- and heat-flow modeling in wellbores, and reservoir engineering. Besides coauthoring more than 125 papers, Kabir coauthored the 2002 SPE textbook Fluid Flow and Heat Transfer in Wellbores and contributed to the 2009 SPE monograph Transient Well Testing.  He has served on various SPE committees, including the editorial review committees for SPEPF, SPEREE, and SPEJ.  He has chaired several ATW and Forum series meetings. He was an SPE Distinguished Lecturer during 2006-2007 and became an SPE Distinguished Member in 2007.  Kabir received the 2010 SPE Reservoir Description and Dynamics award. He currently serves as an associate editor for the SPEREE journal.

Full Description

Many decline-curve analysis methods have emerged for forecasting the future performance of unconventional reservoirs. However, severe noise in field data, coupled with the low-frequency rate in monitoring/reporting and the unknown behavior of many completion and reservoir parameters with time, collectively present serious challenges in obtaining correct model parameters in many settings.

To address the complexity of this multitude of issues, performance forecasting is approached in two steps. First, we attempt to circumvent the data noise and frequency issues with a global cumulative production profile for a group of wells exhibiting similar performance characters, leading to the estimation of global model parameters. Second, we compare error trends amongst all methods for a basis of selecting well groups.

A simple rule-of-thumb is developed to get an estimate of the allowable time for extrapolating performance prediction within certain error bound. This and other studies have shown that at least six months' production data are required for valid extrapolation. Beyond the modern empirical decline-curve methods, this talk also explores the use of tools that have roots in analytical methods.

Organizer Rafael G. Barroeta and Juan Carlos Picott

When?

Thu, Apr. 23, 2015
11:30 a.m. - 1 p.m. US/Central

How Much?

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Where?

Sullivan’s Steakhouse
4608 Westheimer Rd
Houston, TX 77027
United States

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