Reducing Uncertainty in Geostatistical Description with Well-Testing Pressure Data
Albert C. Reynolds, Nanqun He, Dean S. Oliver, 1999. "Reducing Uncertainty in Geostatistical Description with Well-Testing Pressure Data", Reservoir Characterization—Recent Advances, Richard A. Schatzinger, John F. Jordan
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Geostatistics has proven to be an effective tool for generating realizations of reservoir properties conditioned to static data (for example, core and log data, and geologic knowledge); however, in situations when data are not closely spaced in the lateral directions, there will be significant variability in reservoir descriptions generated by geostatistical simulation (that is, significant uncertainty in the reservoir descriptions). Procedures based on inverse problem theory were previously presented for generating reservoir descriptions (rock property fields) conditioned to pressure data and to geostatistical information represented by prior means and variograms for log-permeability and porosity. Although it has been shown that incorporation of pressure data reduces the uncertainty below the level contained in the geostatistical model based only on static information (the prior model), these previous results did not explicitly account for uncertainties in the prior means and the parameters defining the variogram.
This paper specifically investigates how pressure data can help detect errors in the prior means. If errors in the prior means are large and are not taken into account, realizations conditioned to pressure data represent an incorrect sampling of the a posteriori probability density function for the rock properties; however, if the uncertainty in the prior mean is properly incorporated, realistic realizations of the rock property fields are obtained.
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Reservoir Characterization—Recent Advances
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.