The lifetime performance prediction of fractured horizontal wells in tight reservoirs

Abstract

Multiple fractured horizontal wells (MFHWs) are recognised as the most effective stimulation technique to improve recovery from tight and shale gas assets. The performance of MFHWs depends on series of flow regimes developed during production. Understanding of the complex flow behaviour and the proper interpretation of these flow regimes are necessary to obtain information about the reservoirs and to predict the performance of these wells.There are several models available for simulating the early transient linear flow behaviour in unconventional reservoirs. However, they involve over-simplifying assumptions about the hydraulic fracture geometry and the reservoir. Furthermore, these models fail to appropriately consider the compound linear flow regime, the interference effect and/or the transitional periods in between different flow regimes that are expected to be important in such low permeability formations.In this paper, the aim is to investigate the key characteristics of the transient (unsteady-state) flow periods and accordingly propose a practically attractive tool for performance prediction of the MFHWs in tight reservoirs. To achieve this objective, first, series of simulated well test data are discussed to identify the key practical flow regimes that can be expected for various practical MFHWs designs with different fracture spacing, length of fractures etc. Following this investigation, new analytical models are proposed to predict the performance of MFHWs under different dominant transient flow regimes.Moreover, integrating the new models with the pseudo steady state (PSS) productivity index formulation proposed previously by the authors, a new approach is presented that covers the identified flow regimes, i.e. the formation linear, the compound linear and PSS flow regimes and the transition periods in between. The outcome of this study can be used for tasks such as well testing, production performance analysis, forecasting and optimisation of MFHWs design.