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Multiple fractured horizontal wells (MFHWs) are considered as the most effective stimulation technique to improve recovery from low permeability reservoirs particularly tight and shale assets. The understanding of the complex flow behaviour and predicting Productivity Index (PI) of these wells are vital for exploitation of such reservoirs. These data also affect the optimum hydraulic fracture design and the long term well performance. The, analytical or semi analytical, models previously proposed cannot accurately describe the flow behaviour around MFHWs due to lack of capturing the complexity of the flow especially the fracture-to-fracture interference effects. The fine grid three dimensional (3D) simulation approach is also costly and cumbersome. In this work, we followed a novel approach to develop a new equation that can predict MFHWs performance under pseudo-steady state flow conditions in tight reservoirs. An in-house programming code, which automatically creates batch files, reads input data and stores relevant output data for each simulation, was coupled with a fine grid 3D reservoir model to generate the required large data bank. For these simulations, the pertinent parameters (matrix permeability, number of fractures and fracture permeability, spacing, width, length and conductivity) were varied over wide practical ranges based on the full factorial experimental design method. The overall as well as the individual impacts of the parameters on PI, as the output variable, were evaluated by various statistical analyses techniques, including Spearman's rank correlation coefficient, under different prevailing conditions. It is shown, for instance, that increasing the fracture width and permeability does not result in a significant monotonic increase in PI while changing fracture length, spacing and numbers influences PI greatly. Moreover, a new expression is proposed that relates MFHWs-PI to PI of the horizontal well with a single fracture and to number of fractures and dimensionless fracture spacing parameters by applying the symbolic regression technique. The cross validation results show that the proposed equation is general, reliable and simple for prediction purposes because it benefits from limited and appropriate dimensionless numbers with excellent values of fitting indices. This study expands our understanding of flow behaviour in tight reservoirs and provides an invaluable engineering tool that can facilitate simulation of flow around MFHWs and quickly predict their well performance. The new IPR equation can also be used for optimising MFHWs design.

Advanced well completion with multiple, downhole flow control devices such as Inflow Control Devices (ICDs), are a proven and effective solution to mitigate water/gas breakthrough and coning problems in horizontal and multilateral wells. An important parameter adversely affectinthe ICD completion's performance is the annular flow. Such annular flow can be minimised or eliminated by segmenting the wellbore into a number of compartments by installing Annular Flow Isolation (AFI). Installation of sufficient AFI at the optimum locations is a key step in achieving the desired well performance. This number of AFI devices is itself constrained by both costs and risks associated with installing the completion string in a long wellbore of complex geometry. Previous AFI design workflows were based on either a single well parameter or a static well-reservoir model that do not consider the total lifetime benefits of the technology. A new AFI design methodology that accounts for the well's lifetime performance has been developed to ensure optimal AFI design in terms of the location and number of AFI installed along the length of the completion.This novel workflow is based on the concept of, to a degree, mimicking the inflow performance of an "ideal" completion (i.e. the completion where AFI is installed between every 12 m completion joint) with a reduced, realistic number of AFIs. The great advantage of this workflow to optimise the AFI design is that it is based on the well's lifetime production performance while at the same time limiting the computation to a single reservoir simulation run for each number of AFIs. The workflow achieves this by ranking the AFI locations based on a criterion related to the annular pressures. A significant recovery increase can be achieved for wells designed with this new workflow when compared to previously proposed AFI design protocols. The learnings from this study can thus be employed by well engineers to optimally design advanced well completions.

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