Nonparametric Transformations for Data Correlation and Integration: From Theory to Practice
Akhil Datta-Gupta, Guoping Xue, Sang Heon Lee, 1999. "Nonparametric Transformations for Data Correlation and Integration: From Theory to Practice", Reservoir Characterization—Recent Advances, Richard A. Schatzinger, John F. Jordan
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The purpose of this paper is two-fold. First, we introduce the use of non-parametric transformations for correlating petrophysical data during reservoir characterization. Such transformations are completely data driven and do not require an a priori functional relationship between response and predictor variables, which is the case with traditional multiple regression. The transformations are very general, computationally efficient, and can easily handle mixed data types; for example, continuous variables such as porosity, and permeability, and categorical variables such as rock type and lithofacies. The power of the nonparametric transformation techniques for data correlation has been illustrated through synthetic and field examples. Second, we use these transformations to propose a two-stage approach for data integration during heterogeneity characterization. The principal advantages of our approach over traditional cokriging or cosimulation methods are: (1) it does not require a linear relationship between primary and secondary data, (2) it exploits the secondary information to its full potential by maximizing the correlation between the primary and secondary data, (3) it can be easily applied to cases where several types of secondary or soft data are involved, and (4) it significantly reduces variance function calculations and thus greatly facilitates non-Gaussian cosimulation. We demonstrate the data integration procedure using synthetic and field examples. The field example involves estimation of pore-footage distribution using well data and multiple seismic attributes
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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.