This paper continues the investigation of interwell fracturing interference for an infill drilling scenario synthetic case based on Eagle Ford available public data and explores pressure and stress-sink mitigation strategies applied to the simulation cases developed in the previous publication (SPE 174902). Emphasis is given to refracturing scenarios, given the intrinsic restimulation value for depleted parent wells and the strategic importance due to the current low oil prices. The stress and pressure depletion methodology is expanded in this paper, adding a refracturing scenario before the infill child well is stimulated. Changes in stress magnitudes and azimuths caused by new and reactivated fractures are calculated using a finite element model (FEM). After refracturing the parent well, modeling shows that stress deflection and repressurization of the originally depleted production zone will reduce subsequent fracture hits from infill wells. The first mechanism to reduce fracture hits is the stress realignment, which promotes transverse fracture propagation from the infill well away from the parent well. The second fracture-hit-reduction mechanism is repressurization of depleted zones to hinder fracture propagation in lower-pressure zones. Prevention of fracture hits by active deflection results in an increased stimulated reservoir volume (SRV) for both the parent and child wells. Overall pad level and individual wellbore cumulative production experience a significant increase due to increased SRV. With proper reservoir and geomechanical data, this approach can be applied in a predictive manner to decrease fracture-hit risk and improve overall recovery. This workflow represents the first comprehensive multidisciplinary approach to coupling geomechanical, complex hydraulic fracture models, and multiwell production simulation models aimed towards understanding fracture-hit reduction using refracturing. The workflow presented can be applied to study and design an optimum refracturing job to prevent potentially catastrophic fracture hits during refracturing operations.
Summary To investigate interwell interference in shale plays, a state-of-the-art modeling workflow was applied to a synthetic case on the basis of known Eagle Ford shale geophysics and completion/development practices. A multidisciplinary approach was successfully rationalized and implemented to capture 3D formation properties, hydraulic-fracture propagation and interaction with a discrete-fracture network (DFN), reservoir production/depletion, and evolution of magnitude and azimuth of in-situ stresses by use of a 3D finite-element model (FEM). The integrated workflow begins with a geocellular model constructed by use of 3D seismic data, publicly available stratigraphic correlations from offset-vertical-pilot wells, and openhole-well-log data. The 3D seismic data were also used to characterize the spatial variability of natural-fracture intensity and orientation to build the DFN model. A recently developed complex fracture model was used to simulate the hydraulic-fracture network created with typical Eagle Ford pumping schedules. The initial production/depletion of the primary well was simulated by use of a state-of-the-art unstructured grid reservoir simulator and known Eagle Ford shale pressure/volume/temperature (PVT) data, relative permeability curves, and pressure-dependent fracture conductivity. The simulated 3D reservoir pressure field was then imported into a geomechanical FEM to determine the spatial/temporal evolution of magnitude and azimuth of the in-situ stresses. Importing the simulated pressure field into the geomechanical model proved to be a critical step that revealed a significant coupling between the simulated depletion caused by the primary well and the morphology of the simulated fractures within the adjacent infill well. The modeling workflow can be used to assess the effect of interwell interferences that may occur in a shale field development, such as fracture hits on adjacent wells, sudden productivity losses, and dramatic pressure/rate declines. The workflow addresses the complex challenges in field-scale development of shale prospects, including infilling and refracturing programs. The fundamental importance of this work is the ability to model pressure depletion and associated stress properties with respect to time (time between production of the primary well and fracturing of the infill well). The complex interaction between stress reduction, stress anisotropy, and stress reorientation with the DFN will determine whether newly created fractures propagate toward the parent well or deflect away. The technique should be implemented in general development strategies, including the optimization of infilling and refracturing programs, child well lateral spacing, and control of fracture propagation to minimize undesired fracture hits or other interferences.
Determining optimum location of wells is a crucial step in field development. A realistic geological model is an important factor in finding an accurate optimum well location. Usually history matching is used to come up with a realistic geological model. However, there is no unique solution to the history matching problem. Often several geological models could match the history data. This introduces some risk associated with the results of well placement optimization algorithm. In this work, we present a new modified genetic algorithm (GA) for well-placement optimization under geological uncertainty. The inputs of the algorithm are possible geological models, and the level of risk that the user can accept. In the algorithm, the classic GA is modified so that: 1) in evaluating the fitness value (cumulative production or net present value) of each individual (well location) all the possible geological models provided by users are evaluated, 2) upon convergence of the algorithm, the output is one optimum well location as the fittest individual taking into account all the provided geological models, and 3) this optimum well location is selected based on the input user-defined level of risk. Most current available algorithms in the literature do not allow the user to input the risk factor desired and individual weights for each realization. The risk-constrained algorithm will provide different optimum well locations depending on the level of risk the user wants to take. All these features make the new algorithm much more efficient and applied than current well-placement algorithms in the literature for handling geological uncertainty. We present the application of the risk-constrained algorithm to a horizontal well-placement optimization in a gas condensate reservoir, Qatar’s North Field, with multiple possible permeability fields and with different user-defined risk factors.
Determining optimum well locations is a crucial step in field development. Often, broad possibilities and constrains on computational resources limit the scenarios that can be considered. When dealing with heterogeneities, the intuitive engineering judgment may not be sufficient, and use of optimization algorithms becomes necessary in finding a favorable production plan. Although there have been extensive publications on optimization algorithms for oil reservoirs, there is little research aimed at gas or gas condensate reservoirs. In this work, we studied optimization of horizontal well placement in gas condensate reservoirs. One of the current challenges in development of gas condensate fields is condensate blockage. As pressure decreases condensate accumulates around the wellbore, leading to significant reduction in gas production. Horizontal wells can effectively solve this problem. However, due to their high cost, and complex phase behavior determining optimum locations cannot be based only on intuitive judgments. Here we present a horizontal well-placement optimization method for gas condensate reservoirs based on a modified genetic algorithm. Unlike oil reservoirs, the cumulative production in gas reservoirs does not vary significantly (although the variation is not economically negligible) and there are possibly more local optimums. Therefore the possibility of finding better production scenarios in subsequent optimization steps is not much higher than the worse case scenarios, which delays finding the best production plan. In this work, we use a cumulative distribution function to magnify the difference between production scenarios. As a result of this change we were able to find the best scenario with considerably fewer simulations. We apply the modified algorithm to a section of Qatar's North Field, a gas condensate field with the world's largest gas reserves. Our results show that this method can efficiently find the optimum horizontal well locations and can lead to valuable increase in gas and condensate production.
Acid fracturing is the most recognized and successful reservoir stimulation technique for conventional carbonate formations. Resulting fracture conductivity is the key parameter that controls final well productivity, while the competing diffusion and reaction phenomena control the "vital" acid coverage along the full areal extension of the fracture. However, not all reservoirs lend themselves to the same fracture geometry and conductivity, and this is where the "Unified Fracture Design" (UFD) approach is irreplaceable. Classic fracture design optimization with the UFD approach involves the maximization of well productivity. For any mass of proppant to be injected as part of the treatment, the algorithm determines the unique fracture length and width (with height as a parasitic variable) that will provide the maximum productivity index. In this paper we recast the UFD approach for specific acid fracturing applications, where the maximum productivity index is now determined as a function of the optimum fracture geometry determined for any volume of injected acid. The optimum fracture width profile is then obtained by solving the convection-diffusion equation for acid propagation, and subsequently used to study the required acid coverage through the fracture as a function of such optimum fracture width profile. Acid reaction retardation plays a crucial role in ensuring proper acid coverage throughout the optimum fracture length, and this paper focuses on the two major reaction retardation fluid systems: Acid-Internal Emulsions (AIE) and gelled acids. The workflow presented in this paper provides the basis for designing optimum acid fracturing treatments as a function of the volume of acid injected, the acid injection rate and the selected acid retardation method.
To investigate interwell interference in shale plays, a state-of-the-art modeling workflow was applied to a synthetic case based on known Eagle Ford shale geophysics and completion/development practices. A multidisciplinary approach was successfully rationalized and implemented to capture 3D formation properties, hydraulic fracture propagation and interaction with a discrete fracture network (DFN), reservoir production/depletion, and evolution of magnitude and azimuth of in-situ stresses using a 3D finite-element model. The integrated workflow begins with a geocellular model constructed using 3D seismic data, publicly available stratigraphic correlations from offset vertical pilot wells, and openhole well log data. The 3D seismic data were also used to characterize the spatial variability of natural fracture intensity and orientation to build the DFN model. A recently developed complex fracture model was used to simulate the hydraulic fracture network created with typical Eagle Ford pumping schedules. The initial production/depletion of the primary well was simulated using a state-of-the-art unstructured-grid reservoir simulator and known Eagle Ford shale pressure/volume/temperature (PVT) data, relative permeability curves, and pressure-dependent fracture conductivity. The simulated 3D reservoir pressure field was then imported into a geomechanical finite-element model to determine the spatial/temporal evolution of magnitude and azimuth of the in-situ stresses. Importing the simulated pressure field into the geomechanical model proved to be a critical step that revealed a significant coupling between the simulated depletion caused by the primary well and the morphology of the simulated fractures within the adjacent infill well. The modeling workflow can be used to assess the effect of interwell interferences that may occur in a shale field development, such as fracture hits on adjacent wells, sudden productivity losses, and drastic pressure/rate declines. The workflow addresses the complex challenges in field-scale development of shale prospects, including infilling and refracturing programs. The fundamental importance of this work is the ability to model pressure depletion and associated stress properties with respect to time (time between production of the primary well and fracturing of the infill well). The complex interaction between stress reduction, stress anisotropy, and stress reorientation with the DFN will determine if newly created fractures propagate toward the parent well or deflect away. The technique should be implemented in general development strategies, including the optimization of infilling and refracturing programs, child well lateral spacing, and control of fracture propagation to minimize undesired fracture hits or other interferences.
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