Evaluation of Field Development Plans Using 3-D Reservoir Modeling
D. Seifert, J.D.H Newbery, C. Ramsey, J.J.M. Lewis, 1999. "Evaluation of Field Development Plans Using 3-D Reservoir Modeling", Reservoir Characterization—Recent Advances, Richard A. Schatzinger, John F. Jordan
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Three-dimensional reservoir modeling has become an accepted tool in reservoir description and is used for various purposes, such as reservoir per-formance prediction or integration and visualization of data. In this case study, a small northern North Sea turbiditic reservoir was to be developed with a line-drive strategy utilizing a series of horizontal producer and injector pairs, oriented north-south. This development plan was to be evaluated and the expected outcome of the wells was to be assessed and risked.
Detailed analyses of core, well log, and analog data have led to the development of two geological end member scenarios, thus accounting for uncertainties associated with the geological model. Both scenarios have been modeled using the sequential indicator simulation method in a hybrid deterministic-stochastic approach. The resulting equiprobable realizations have been subjected to detailed statistical well placement optimization and analysis techniques. Based upon bivariate statistical evaluation of more than 1000 numerical well trajectories for each of the two scenarios, it was found that the inclinations and lengths of the wells had a greater impact on the wells' success, whereas the azimuth was found to have only a minor impact. After integration of these results, the actual well paths were redesigned to meet external drilling constraints, resulting in substantial reductions in drilling time and costs.
Although three development wells drilled subsequent to this study were very successful, their outcome raises questions about the validity of the stochastic model, which is based on geological assumptions which, in turn, were derived from much fewer well data. It is clear that a better quantitative sedimentological understanding of the reservoir, specifically in the lateral dimension, would have resulted in a more reliable reservoir model.
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Optimum reservoir recovery and profitability result from guidance by an effective reservoir management plan. Success in developing the most appropriate reservoir management plan requires knowledge and consideration of (1) the reservoir system, including rocks, fluids, and rock-fluid interactions, as well as wellbores and associated equipment and surface facilities; (2) the technologies available to describe, analyze, and exploit the reservoir; and (3) the business environment under which the plan will be developed and implemented. Reservoir management plans de-optimize with time as technology and the business environment change or as new reservoir information becomes available. Reservoir characterization is the process of creating an interdisciplinary high-resolution geoscience model that incorporates, integrates, and reconciles various types of geological and engineering information from pore to basin scale. The reservoir data are then conceptually and quantitatively modeled and compared to the historical production data and fluid flow distribution patterns within and beyond the limits of the reservoir to match well production histories and predict their behavior. The goals of reservoir characterization are to simultaneously (1) maintain high displacement efficiency, (2) optimize high sweep efficiency, (3) provide reliable reservoir performance predictions, and (4) reduce risk and maximize profits. Notice that in addition to the technical concepts that we normally associate with "characterization," maximizing profits is an essential element of this process. Papers from the Fourth International Reservoir Characterization Technical Conference (1997), sponsored by the U.S. Department of Energy, this publication is a unique compilation of 27 papers covering every aspect of reservoir characterization and has been a popular AAPG publication since that time. Using an interdisciplinary approach, the papers address qualitative information as well as integrated quantified data and culminate in a fully integrated study.