The study provides insights into the development of a data-driven model for hydraulic fracturing design optimization. We make a specific focus on practical aspects of testing the model in the field. Database for hydraulic fracturing treatments is built on the data from 22 oilfields in Western Siberia, Russia. The database contains about 5500 points with formation, well and fracturing process parameters, the target feature for model is a cumulative fluid production for 3 months. System and method for searching offset (similar) wells is also developed, tested and validated. Authors developed the model for predicting cumulative production that is used for futher hydraulic fracturing design optimization.
The paper considers a semi-analytical model for the water-injection well critical pressure estimation at which the fracture will initiate. The model is based on the Biot`s theory of poroelasticity and the algorithm based on the Fourier transforms and the finite difference method was used to solve the problem. The solution involves a sequential calculation of changes in the reservoir pressure distribution and changes in rock stresses using plane-stress approach for a periodic development element. For the cases when the assumption of the homogeneity of the elastic, strength and formation reservoir properties is unacceptable three-dimensional geomechanical modeling algorithm is used, taking into account the actual geological parameters of the formations and the results of hydrodynamic modeling using historical data. In addition, a semi-analytical model for the water-induced fracture breakthrough interval (in height) estimation is proposed. The model includes the following parameters: formation pressure, injection speed, fluid viscosity and injection time. The model is based on the net pressure calculation for a rectangular hydraulic fracture in the leakage dominant regime (Perkins–Kern–Nordgren model). The model uses a 1D geomechanical model and reservoir properties as an input data. The breakthrough interval is calculated iteratively with the assumption of the fracture height at each step. The additional net pressure is calculated using the distribution of permeability and formation elastic properties. If this pressure exceeds the compressive rock stresses in the neighboring layers, then the water-induced fracture will grow vertically into the neighboring layers. The iteration continues until the vertical growth stops. The resulting techniques can be used for waterflooding process control and development system optimization.
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