Results of the Brugge Benchmark Study for Flooding Optimization and History Matching

Abstract

Summary In preparation for the SPE Applied Technology Workshop (ATW) held in Brugge in June 2008, a unique benchmark project was organized to test the combined use of waterflooding-optimization and history-matching methods in a closed-loop workflow. The benchmark was organized in the form of an interactive competition during the months preceding the ATW. The goal set for the exercise was to create a set of history-matched reservoir models and then to find an optimal waterflooding strategy for an oil field containing 20 producers and 10 injectors that can each be controlled by three inflow-control valves (ICVs). A synthetic data set was made available to the participants by TNO, consisting of well-log data, the structure of the reservoir, 10 years of production data, inverted time-lapse seismic data, and other information necessary for the exercise. The parameters to be estimated during the history match were permeability, porosity, and net-to gross- (NTG) thickness ratio. The optimized production strategy was tested on a synthetic truth model developed by TNO, which was also used to generate the production data and inverted time-lapse seismic. Because of time and practical constraints, a full closed-loop exercise was not possible; however, the participants could obtain the response to their production strategy after 10 years, update their models, and resubmit a revised production strategy for the final 10 years of production. In total, nine groups participated in the exercise. The spread of the net present value (NPV) obtained by the different participants is on the order of 10%. The highest result that was obtained is only 3% below the optimized case determined for the known truth field. Although not an objective of this exercise, it was shown that the increase in NPV as a result of having three control intervals per well instead of one was considerable (approximately 20%). The results also showed that the NPV achieved with the flooding strategy that was updated after additional production data became available was consistently higher than before the data became available.

A review of closed-loop reservoir management

“…After history-matched reservoir models were created, water flooding strategies for 20 producers and 10 injectors were optimized. Peters et al (2010) have summarized in detail the results of the Brugge test case obtained by nine research groups. Briefly, Table 1 compares the reservoir simulators, optimization methods, and the net present values optimized in Year 10.…”

Advanced Integrated Workflows for Incorporating Both Production and 4D Seismic-Related Data into Reservoir Models

“…The Brugge test case is a synthetic oil field built for benchmarking purposes (Peters et al, 2009). We shortly describe the available dataset and explain the procedure developed to match the target production data.…”

“…Besides, several random geological realizations were generated from well logs from various stochastic simulation schemes. At last, Peters et al (2009) delivered 104 realizations defined over a grid with 60 000 cells and consisting of nine layers (two in Schelde, three in Waal, three in Maas, and one in Schie). To sum up, the available data were the well logs, the first 10 years of production history and the 104 random realizations generated on a coarser grid.…”

“…The following sections present two application cases. The first one is the "Brugge field" prepared for benchmarking purposes (Peters et al, 2009): the dataset to be matched encompasses 10 years of production history. The second case is also a synthetic case built from a real field.…”

Next Generation Geological Modeling for Hydrocarbon Reservoir Characterization

“…Knowledge of the proportions is not sufficient for accurate modeling of the lithotypes and the depositional system templates help modelers to visualize relationships between the facies and to provide an associated lithotype "rule box" (see: upper left schematics, Fig. 5 and facies-constrained model of porosity distribution of Brugge synthetic model (Peters et al, 2009), generated by DecisionSpace  Desktop Earth Modeling.…”