A DECISION SUPPORT SYSTEM FOR IMPROVING HYDRAULIC FRACTURE TREATMENT FOR HYDROCARBON RESERVOIRS

Abstract

This paper presents a complete decision support system for designing a hydraulic fracture treatment program, with comprehensive reasoning at every stage. The overall hydraulic fracturing design problem is viewed as a multi-objective and multivariate system design problem, which recognises complex interactions between a hydraulically coupled fracture geometry model, a hydrocarbon production model and an investment-return cash flow model. The selected models have been incorporated into the system based on critical assessments against other alternative models in terms of their degree of uncertainty and suitability for particular design cases.

Based on critical analysis of the overall system, free design variables (the values of which have to be decided) are identified. System constraints are formulated to ensure that the values of these design variables are selected within their specified ranges, based on experience, industry practice and other system considerations. These constraints also ensure that any final design is executable in the field using the specified surface equipment (pump, tube, etc.) and that the treatment does not cause any undesirable formation damage by uncontrolled fracture growth and/or multiple secondary fracture initiation.

Various measures of merit, such as production, net present value and treatment cost, are used to assess a design; possible conflicts between them are discussed. Finally, an innovative prioritised goal-set combined objective function is proposed to achieve a goal-oriented hydraulic fracturing treatment program. Possible solution tools, which can manage such a complex problem, are reviewed in order to achieve an optimum design. A novel intelligent moving object algorithm is introduced to develop a scheme for optimising the design of a hydraulic fracture stimulation program. The reasoning and action sequence of this algorithm is presented in simplified formulations rather than as complex mathematics. By simple reasoning and action, the algorithm improves an initial given design towards a compromised best possible design satisfying all the constraints. The algorithm is capable of handling any degree of non-linearity, nondifferentiability and discontinuity in the objective and constraint functions formulated by the use of production and cost-return models and knowledge of complex fracture geometry.

The overall decision support system is applied to a tight gas reservoir from central Australia. Results show that the proposed system improves hydraulic fracturing design and provides a goal-oriented optimum design in a conflicting environment. Of particular interest is that about 12% compromise with maximum possible production, or net present value (NPV) over 10 years can save up to 44% of initial hydraulic fracturing treatment cost. Although the dollar value of NPV sacrifice is more than the treatment cost saving, a company may still prefer such a design because it offers immediate cash saving compared to marginal NPV sacrifice over a period that may encounter various uncertainties. However, the 88% production, or net present value, as a result of an optimum treatment program designed by the proposed optimisation scheme is significantly higher than any arbitrary design.