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Decisions regarding problem conceptualization, search approach, and how best to parametrize optimization methods for practical application are key to successful implementation of optimization approaches within georesources field development projects. This work provides decision support regarding the application of derivative-free search approaches for concurrent optimization of inflow control valves (ICVs) and well controls. A set of state-of-the-art approaches possessing different search features is implemented over two reference cases, and their performance, resource requirements, and specific method configurations are compared across multiple problem formulations for completion design. In this study, problem formulations to optimize completion design comprise fixed ICVs and piecewise-constant well controls. The design is optimized by several derivative-free methodologies relying on parallel pattern-search (tAPPS), population-based stochastic sampling (tPSO) and trust-region interpolation-based models (tDFTR). These methodologies are tested on a heterogeneous two-dimensional case and on a realistic case based on a section of the Olympus benchmark model. Three problem formulations are applied in both cases, i.e., one formulation optimizes ICV settings only, while two joint configurations also treat producer and injector controls as variables. Various method parametrizations across the range of cases and problem formulations exploit the different search features to improve convergence, achieve final objectives and infer response surface features. The scope of this particular study treats only deterministic problem formulations. Results outline performance trade-offs between parallelizable algorithms (tAPPS, tPSO) with high total runtime search efficiency and the local-search trust-region approach (tDFTR) providing effective objective gains for a low number of cost function evaluations. tAPPS demonstrates robust performance across different problem formulations that can support exploration efforts, e.g., during a pre-drill design phase while multiple independent tDFTR runs can provide local tuning capability around established solutions in a time-constrained post-drill setting. Additional remarks regarding joint completion design optimization, comparison metrics, and relative algorithm performance given the varying problem formulations are also made.
Decisions regarding problem conceptualization, search approach, and how best to parametrize optimization methods for practical application are key to successful implementation of optimization approaches within georesources field development projects. This work provides decision support regarding the application of derivative-free search approaches for concurrent optimization of inflow control valves (ICVs) and well controls. A set of state-of-the-art approaches possessing different search features is implemented over two reference cases, and their performance, resource requirements, and specific method configurations are compared across multiple problem formulations for completion design. In this study, problem formulations to optimize completion design comprise fixed ICVs and piecewise-constant well controls. The design is optimized by several derivative-free methodologies relying on parallel pattern-search (tAPPS), population-based stochastic sampling (tPSO) and trust-region interpolation-based models (tDFTR). These methodologies are tested on a heterogeneous two-dimensional case and on a realistic case based on a section of the Olympus benchmark model. Three problem formulations are applied in both cases, i.e., one formulation optimizes ICV settings only, while two joint configurations also treat producer and injector controls as variables. Various method parametrizations across the range of cases and problem formulations exploit the different search features to improve convergence, achieve final objectives and infer response surface features. The scope of this particular study treats only deterministic problem formulations. Results outline performance trade-offs between parallelizable algorithms (tAPPS, tPSO) with high total runtime search efficiency and the local-search trust-region approach (tDFTR) providing effective objective gains for a low number of cost function evaluations. tAPPS demonstrates robust performance across different problem formulations that can support exploration efforts, e.g., during a pre-drill design phase while multiple independent tDFTR runs can provide local tuning capability around established solutions in a time-constrained post-drill setting. Additional remarks regarding joint completion design optimization, comparison metrics, and relative algorithm performance given the varying problem formulations are also made.
E&P operators are looking at innovative solutions to control water production in horizontal oil well producers, to maximize their assets’ value. The operators are putting greater emphasis on maximizing oil production from the existing assets instead of performing sidetrack or drilling new wells. Completing wells with equalizer completions; inflow control device (ICD) separated by openhole packers is one such solution. Two kinds of equalizers are used for entry of wellbore fluids; Active ICDs and Passive ICDs. For wells completed with Active ICDs, a shifting tool can be used to close the water producing ICDs. However, for wells completed with passive ICDs, plugs with cement can be used, which will isolate the section below, leaving much of the oil behind. For wells in which the heel or the middle section starts to produce water, there was no solution, but to live with it or re-sidetrack the well. Recently, a new technology of expandable steel technology has been selected, and specifically customized for ICDs isolation purposes. The patch is corrosion resistant alloy (CRA) material, which was selected to cope with the harsh corrosive environment. Pipe geometry had to be adjusted to enable "Patch thru Patch" capacity. Despite the tight restrictions of the well, the use of this technology allowed to keep enough clearance after installation to pass another Patch thru later on, if required. Prior to performing the isolation of the ICD, production logs of the horizontal section were carried out to analyze the production and locate precisely the high-water producing zones. Three (3) Patches were successfully deployed rigless using smart coiled tubing. The real time monitoring enabled accurate positioning and smooth down hole pressure control. Post patch installation, wellbore path remained clear, enabling production from the bottom zone. The well performance improved with substantial reduction in water production and consequent incremental increase in the oil production. Isolating the dominating water contributing ICDs, contributed to increase the oil contribution from the other ICDs. This was confirmed by another production log performed post patch installation. This was the first installation of Xpandable Steel Patch across ICD's worldwide. This paper will highlight the technology and its application, solution selection process and the operational deployment of the Xpandable Steel Patch including real-time monitoring capabilities of instrumented Coil tubing (CT) which can be leveraged to accurately install the patches.
To quantify the uncertainty in reservoir performance, it is common to build ensembles of models that sample the space of possible reservoirs that are consistent with the available data. To evaluate the spread of possible outcomes, simulations experiments are run for each model in the ensemble to calculate for instance recovery factor. The geoscreening workflow is a common way to do this systematically and in a reasonable time. It can work as follows: First, run simulations with simplified physics to calculate recovery factor for every model in the ensemble. Then, use recovery factor (and other quantities) to rank and select representative models for high, medium, and low performance scenarios that can be used for full field simulations. In this paper we present an application of the multiscale sequential fully implicit (MS SFI) framework to simulate extremely complex high-resolution models with simplified physics. This enables us to perform fast evaluations of geological uncertainty, such as in the geoscreening workflow. The multiscale SFI method computes each timestep in two steps: First, it solves a nonlinear equation for pressure (and flow). Then, it solves a nonlinear equation for saturations and mole fractions. The pressure equation is solved iteratively using a multiscale approach. The MS SFI method has recently been made generally available in a commercial reservoir simulator and can easily be benchmarked with a state-of-the-art fully implicit (FI) method. The MS SFI method was used to successfully simulate a realistic high-resolution geological model in a practical time frame, achieving approximately 10 times speedup in CPU time compared to the FI method. This demonstrates the ability of the MS SFI method to effectively deal with extremely complex models, enabling fast quantification of geological uncertainty with a shorter turnaround time. In many instances the MS SFI method enables simulation of large models at the original geological resolutions without the need for upscaling. Finally, we demonstrate how the MS SFI method benefits a geology screening workflow and discuss future use of the MS SFI framework to create fit-for-purpose simulation engines for other workflows.
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