A Flownet-Based Method for History Matching and Production Prediction of Shale or Tight Reservoirs with Fracturing Treatment

Abstract

Summary Based on a newly developed physics-based data-driven model FlowNet, this paper presents an effective method for history matching and production prediction of fractured shale or tight reservoirs without any prior information about fracture geometry. In this method, four types of well nodes including fracturing cluster nodes, fracture nodes, stimulated reservoir volume (SRV) nodes, and matrix nodes are allocated in the reservoir. Then, the reservoir model is simplified as a flow network composed of some 1D connection elements between these nodes. Some grids are divided on each connection element, and the grids on the same connection element are of equal width and permeability. Subsequently, a fully implicit nonlinear solver is used to solve flow equations in this FlowNet grid system to obtain pressure, phase saturation, and production rates, etc. Efficient history-matching procedure based on the FlowNet model of the fractured reservoir is used to determine the parameters of connection elements, and then fast production prediction can be conducted. Five numerical examples including single-well depletion, waterflooding development with natural fractures, multiple-well interference, three-phase flow, and an actual waterflooding field case validate that this presented FlowNet-based method can achieve good history matching and production prediction for various flow problems in shale or tight reservoirs with fracturing treatment, and the history-matched transmissibility and volume of connection elements can reflect the existence of high-conductivity fractures.