Completing wells with multiple pay sections can be difficult and costly. With limited capital allocated at completion time, the geologist and the completion engineer are faced with deciding how to spend the available funds to attain the best return on investment (ROI) or net present value (NPV).

A process has been developed for selecting and ranking multiple pay sections and for giving accurate post-stimulation production estimates with advanced logging technology, such as magnetic resonance imaging (MRI), in conjunction with a production reservoir simulator.

This process ranks multiple pay sections by hydrocarbon storage capacity (ϕeff)(h), and producing capacity (kh). Initial productions (IP's), Estimated Ultimate Recoveries (EUR's), or projected cumulative production is then predicted for each section with variable stimulation half-lengths (Xf) or skin values (S). Output can be displayed on the log or in a tabular format.

NPV, ROI, or the internal rate of return (IRR) can be estimated for each stimulation scenario. These estimations can help operators justify stimulation job size and completion cost for each section of pay selected, giving the operator an additional tool for deciding how to best spend completion dollars.

The ranking process can be performed rapidly, and it provides a producing potential before setting pipe. This paper illustrates the process with six field examples from the Granite Wash formation in the Ammunition Field of Washita County, OK. Actual production is compared to predicted production for each well.

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