Abstract

Abstract This article presents the development of the UNISIM-I-M benchmark case, a set of simulation models representing the field and the information required for a decision-making analysis in the oil field management phase, giving continuity to UNISIM-I benchmark studies. Using the feedback from previous benchmark cases (UNISIM-I-D, UNISIM-I-R), we present a proposal specifically for the management phase, i.e., the period after strategy implementation. UNISIM-I-M is designed for research activities in decision analysis to select exploitation strategies during the reservoir's management phase. This work presents the results of the construction of this benchmark and information on how it can be used. UNISIM-I-M considers an exploitation strategy already in place in the initial stage of field development and a water-flooding project with 25 wells with history production data for the first 7 years. Uncertainties include structural models, PVT, oil-water contact, water relative permeability, vertical permeability multiplier, rock compressibility, 500 images with petrophysical characteristics related to facies, net-to-gross ratio, porosity, horizontal and vertical permeabilities, systems availability, and economic scenarios. The simulation model, with affordable simulation time, is based on a reference model reflecting the characteristics of Namorado Field, Campos Basin in Brazil, comprising real and synthetic data from the appraisal phase. Based on a geological model, we used a Discretized Latin Hypercube with geostatistical realizations to sample and combine different types of uncertainties (continuous and discrete attributes and realizations represented by geostatistical images) to generate 2000 possible scenarios. We then applied a probabilistic history-matching process to reduce the number of scenarios. The misfit between the models and the production history data was evaluated by quantification and diagnostic procedures, considering acceptance levels and several objective functions simultaneously, including well-fluid rates and bottom-hole pressures. This yielded a set of 48 scenarios honoring the history data and considering all uncertainties to compose UNISIM-I-M. This benchmark proposes the optimization of future design and/or control variables of the exploitation strategy for the remaining 23 years, such as infill drilling, recompletion, well conversion, conditions for shutting wells, and intelligent valves. To develop the benchmark, the studies should consider deterministic and probabilistic approaches using reservoir simulation, economic and risk analysis. All main probabilistic parameters are specified to allow a complete evaluation. We present one solution for validation. To conclude, UNISIM-I-M enables tests, application, validation of existing and new methodologies and a comparison of the results of research institutes, universities and oil companies regarding optimization and risk analysis techniques. UNISIM-I-M takes on special importance due to the lack of benchmark cases with known answers and complete reservoir models comprising geological, operational and economic scenarios. It provides challenges to test techniques for decision analysis in the management phase to the uncertainties, complexity and constraints involved and the nature of the design and control variables. The dataset is publicly available via webpage. Participants are encouraged to discuss methods, results and challenges to validate different procedures for the selection of the management strategy. To enable a fair comparison, a set of results and data with complete documentation of assumptions should be reported.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.