A framework for history matching - StreamSim Technologies, Inc.

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Mepo significantly reducing the turnaround time to update models The Multipurpose Environment for Parallel Optimisation (Mepo), is designed to support the process of History Matching in Reservoir Engineering. While the turnaround time for creating new and updating old models has been significantly reduced, the reservoir engineer still has to validate the model through history matching and uncertainty assessment, before generating production forecasts. Most oil companies spend a significant amount of time in creating geological models for reservoir simulation. Significant resources are consumed when adapting to multidisciplinary work and integrated reservoir modeling work- flows. While recent software developments have reduced the modeling time tremendously, the history matching or model validation task is still cumbersome and very time-consuming. If you cannot match the observed data to your simulation model, the history matching process can exceed the time used to create or update the reservoir model by a factor of 10. Furthermore, if you do not have the capacity for additional history matching, you will probably pick the apparent best match so far, and use this model for production forecasting. Bad decisions are often taken due to the large uncertainties in the model, e.g. drilling of wells missing reservoir targets. What if the history matching and uncertainty assessment could be performed quickly and at a low cost? Mepo, a new software framework, is revolutionising history matching by reducing manpower requirements and assessing the uncertainty of simulation models. Recent studies show a reduction in modeling time of more than 50%.
Mepo a framework for history matching Mepo is an invaluable tool and framework for the reservoir engineer performing history matching (HM). The benefits offered by Mepo are explained below. I. A match will be found A simulation model with a poor match can give misleading results. Planning new wells with a low risk of missing the reservoir is of paramount importance. In addition, a well matched model will be reliable to the extent that it can be used in decline analysis and other predictions of future field performance. Mepo optimises model parameter sets until convergence is reached, i.e. until a match is obtained. Even in cases in which convergence is not reached, Mepo offers concepts and methods to investigate the solution space and to provide information on changing the HM strategy. Implementing Mepo in the HM-workflow will define a guideline and facilitate the process to get a match. II. Assessing the viability of the simulation model In order to increase the acceptance of results from the simulation model, the uncertainty of any acceptable HM result should be quantified. When a model reproduces all history properly, the HM is considered acceptable. However, due to the nature of the problem, there are a number of acceptable solutions. Each solution might generate different predictions. Mepo investigates the model diversity, which can give insights into the model uncertainty. Mepo includes global optimisation methods, which have the potential to identify various good matches. A number of acceptable matches can be used for prediction runs. Differences in the predicted results reflect and quantify the model uncertainty. This approach goes far beyond the linear perturbation of parameter values based on one acceptable match. The method adds value by quantifying uncertainty and increasing reliability on the reservoir model used for reservoir predictions. Mepo supports the identification of several acceptable matches to assess the uncertainty of the simulation model. Several simulations fall within an acceptable uncertainty range in the history period, but the predictions from the same models define an uncertainty in the simulated production forecast.
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Page 11 and 12: The Mepo workflow

A framework for history matching - StreamSim Technologies, Inc.

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