Sand control by hydraulic fracturing in high permeable gas formation is becoming an increasingly popular completion option. This improves the well’s productivity as well as manages the sand production. So, optimizing the treatment parameters for hydraulic fracturing, which can prevent most unfavorable effects, one of them being sand production, is now a critical process to be programmed systematically with all realistic design constraints. This paper describes the development of an integrated program with global optimization algorithms that optimize all treatment parameters simultaneously; maximizing objective function (net present value) and satisfying newly modeled design constraints. These constraints are formulated as functions of treatment parameters, fracture geometry, and mechanical and petrophysical properties of the reservoir, so that the critical conditions that induce sand production and other unfavorable effects do not become active. One of the important constraints is the critical drawdown pressure (CDP) relating to sand production. A genetic-evolutionary computing algorithm is integrated to solve the constrained treatment design problem that it finds optimum values for treatment parameters and fracture geometry that are formation compatible. The capability of the integrated model is demonstrated by application to a hypothetical gas reservoir and predicting the production and CDP over a number of years, helping sand control. When compared with the proposed model, the traditional model violates some important constraints.

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