Abstract
Hydraulic fracturing is widely used to determine in situ stress of rock engineering. In this paper we propose a new method for simultaneously determining the in situ stress and elastic parameters of rock. The method utilizing the hydraulic fracturing numerical model and a computational intelligent method is proposed and verified. The hydraulic fracturing numerical model provides the samples which include borehole pressure, in situ stress, and elastic parameters. A computational intelligent method is applied in back analysis. A multioutput support vector machine is used to map the complex, nonlinear relationship between the in situ stress, elastic parameters, and borehole pressure. The artificial bee colony algorithm is applied in back analysis to find the optimal in situ stress and elastic parameters. The in situ stress is determined using the proposed method and the results are compared with those of the classic breakdown formula. The proposed method provides a good estimate of the relationship between the in situ stress and borehole pressure and predicts the maximum horizontal in situ stress with high precision while considering the influence of pore pressure without the need to estimate Biot’s coefficient and other parameters.
Highlights
Hydraulic fracturing is widely used in the recovery of oil, gas, geothermal, and mineral resources [1]
In petroleum engineering it is important to determine the in situ stresses and elastic parameters of the rock mass when using hydraulic fracturing in fracturing operations, wellbore stability analysis, and reservoir simulation [2]
Owing to the limitations of the classic breakdown formulae and the complexity of hydraulic fracturing tests, laboratory and field tests have been commonly used to determine the in situ stress and mechanical parameters of rock mass (Algorithm 1)
Summary
Hydraulic fracturing is widely used in the recovery of oil, gas, geothermal, and mineral resources [1]. Owing to the limitations of the classic breakdown formulae and the complexity of hydraulic fracturing tests, laboratory and field tests have been commonly used to determine the in situ stress and mechanical parameters of rock mass (Algorithm 1). These tests may not always produce the poroelastic parameters or may provide inaccurate results. Zhang and Yin proposed a back analysis method which combined a neural network and a genetic algorithm to simultaneously identify the in situ stresses and elastic parameters [2]; this method did not consider the poroelastic effect To overcome this difficulty, in this paper we extend our proposed displacement back analysis method to determine the in situ stress and mechanical parameters of a rock mass based on measured borehole pressure.
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