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Abstract Fracture stimulation production response coupled with the hydrocarbon sales price determines the value of a fracture stimulation treatment. Many factors can significantly effect the production response of a fracture stimulated well. Some examples include stimulation fluid selection, proppant selection, pumping rates, rock properties, reservoir fluid properties, in-situ stresses, stress variations, on-site execution, post-treatment stimulation fluid recovery, and operating practices. The production response in economic terms portrays the net effect of these variables. This paper presents a case study that demonstrates how post-treatment evaluations expressed in economic terms can be used to assess the performance of stimulations and to guide future design choices. Introduction Methods of evaluating fracture stimulation treatments range from comparing offset well performance, comparing pre- and post-treatment well tests and/or production response, to using type curves, analytical models, and numerical simulation. Some techniques even combine aspects of several of the above mentioned methods to increase the chances of arriving at a unique solution. The results of the methods range from relative performance comparisons to detailed analysis of reservoir and fracture flow parameters. While these assessments are useful to varying degrees, none of them attempt to make a meaningful evaluation and comparison in economic terms. The net present value versus infinite conductivity fracture half-length (NPV vs Xfi,) plot is one tool which can help to optimize fracture stimulation treatment designs. Ideally, an economic comparison of fracture stimulation treatments accounts for treatment costs, reservoir fluid and rock properties, operating practices, and the myriad of stimulation treatment variables. Although the treatment design may be based on subjective analysis of the NPV curve, maximizing NPV vs Xfi is a valid tool if good estimates for reservoir parameters can be made prior to the stimulation treatment. The fracture model selected will also influence the design expectations. The impact of this variable on pre-fracture design expectations is presented. The NPV vs Xfi plot can also be used, post-fracture, to assess the success of the stimulation treatment. By using reasonable ranges of reservoir parameters, the actual net present values and effective fracture half-lengths of similar wells can be plotted together for a rapid visual comparison. Including fracture treatment efficiency curves on the plot helps quantify the level of success of the treatment. In this study, the fracture treatment efficiency curves represent the NPV as a function of the ratio of the effective fracture half-length to the design fracture half-length. One minor concern in the post-fracture evaluation is the reliability of estimates for the infinite conductivity fracture half-length. Pressure build-up tests are expensive in terms of deferred production and the tests frequently are not uniquely interpretable. Constant rate draw-down tests can be difficult to conduct and also have a deferred production component. A more cost effective approach is needed. Evaluation of reservoir parameters and well geometry through analysis of production data has been demonstrated by several authors. Recording daily producing rates and pressures enables an analysis to be conducted early in the life of a well. The production data analysis should consider the expected reservoir parameters, the design and execution of the stimulation performed, and the operating practices. This approach is used to estimate the effective fracture half-lengths for this study. The goal is to maximize the value of a well or a field. Since optimizing stimulation design is an iterative process, a decision loop must be developed to evaluate and refine the assumptions. The decision loop starts with an initial design based on a specific economic goal. This is followed by careful execution of the treatment to ensure proppant placement. P. 45 |
