Petroleum reservoir simulation and characterization system...

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science

Reexamination Certificate

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C702S014000

Reexamination Certificate

active

06826483

ABSTRACT:

BACKGROUND OF THE INVENTION
The present invention relates to systems and methods for the evaluation and modeling of mineral reservoirs, and in particular to methods and systems for providing in a single, remotely-accessible computer middleware and interface for the efficient movement of disparate data and processing outputs among and between several software applications used for the comparative analysis and prediction regarding the characteristics over time of withdrawal of petroleum reservoir fluid (crude oil, gas, and water) using any or all among seismic, well logs, production data and other geological, geophysical, and petroleum engineering data and analyses that might be relevant.
In the petroleum exploration and production sector, a priority is placed on gaining accurate knowledge and analysis regarding the characteristics and changes over time of petroleum reservoirs (for instance, reservoirs of crude oil and/or natural gas) as oil, gas, and water are being extracted at the surface. Because petroleum deposits occur underground, often far below the surface of the Earth (one to several miles), and because the contents of a petroleum reservoir (for instance, an oil or gas field) may be dispersed throughout a spatially and geologically extensive and diverse underground region (the reservoir), the evaluation over time of petroleum reservoirs is a complex and economically essential task.
The goals of evaluating reservoirs are manifold and begin with the earliest stages of speculative exploration activity (at a point when it is not necessarily known whether a geologic region or structure contains accessible petroleum in commercially marketable quantities), through the production lifetime of an identified reservoir (when it may be important, for example, to evaluate and/or vary the best sites for placing wells to tap the reservoir, or the optimal rate at which petroleum may be removed from a reservoir during ongoing pumping). Because companies in the petroleum industry invest very large sums of money in exploration, development, and exploitation of potential or known petroleum reservoirs, it is important that the evaluation and assessment of reservoir characteristics be accomplished with the most efficient and accurate use of a wide range of data regarding the reservoir.
To this end, geologists, geophysicists, and petroleum engineers have developed numerous methodologies for assessing petroleum reservoirs (as to such parameters as total reserves, location of petroleum, pressure decline, water encroachment, gas dissolution, etc.). These methodologies have relied upon a wide range of software applications, to which are input data variables regarding the geological character of the reservoir and how these data variables vary over the time of production.
Many of these data variables can be gauged most readily by analysis of seismic data—i.e., data obtained by analysis of the characteristics of sound waves travelling through and reflected from underground geological structures. Because, as is well known, sound travels with different speeds through different substances—e.g., fluid filled, porous rock of different densities—seismic analysis of sound waves caused to travel through a petroleum reservoir can be used to characterize that reservoir in terms of its heterogeneous constituent parts; e.g. the various solid, liquid, etc. regions or components of the reservoir and their respective locations within the reservoir can be mapped as they change over time. The term SeisRes may be used generally throughout herein to refer to data and processes for characterizing petroleum reservoirs (typically by seismic means), though it must be understood that input physical data other than, or in addition to strictly seismic data can be and is used in evaluating, analyzing, and forming characterizations of subsurface regions and petroleum reservoirs. The present invention is particularly useful for, but is not limited to, characterization techniques focusing in large part on seismic data; it can also manage and optimize characterization using other types of data inputs. Reservoir evaluation and characterization generically (including but not limited to that using seismic, non-seismic, and hybrid data analysis) will be referred to herein as SeisRes OF. The middleware and interface system we call the operating framework, henceforth abbreviated (OF).
Obviously such data may be of use in, for instance, confirming and characterizing the location of, say, liquid petroleum within the reservoir, thus potentially easing greatly its quantification and extraction.
Because Exploration & Production (“E&P”) operations in the energy industry are worldwide, rural as well as urban, and highly technical, employing a diverse set of scientific, business and engineering data sets and software applications, improvements in efficiency of reservoir evaluation processes are exceedingly complex and difficult. While various computer-driven applications for analysis of petroleum reservoirs have been known, evaluation, quantification, and characterization of a given reservoir will almost always require analysis under more than one computer application. The key software applications (apps) have different sources, vendors, formats, languages, and data protocols. In many cases, the plurality of computer applications may be designed for disparate operating systems, may apply different processing algorithms or analytic assumptions, and may use input data and/or supply processed output data in formats (e.g., data input/output formats using different measurement units, benchmarks, time frames, or terminology, sets of variables) that are not consistent with the respective data formats used by another computer analysis application being applied to the same reservoir. Hence, while useful computer analysis applications have been known, the process of feeding raw input data about a reservoir into the disparate applications (which in some cases may involve feeding partially- or fully-processed data or results from one application into another application for further processing), and thereafter of efficiently processing by the plurality of applications to obtain preliminary output data or characterizations of the petroleum reservoir (i.e., of the state, location, and volume quantity of substances within the reservoir, specifically of petroleum fluids), and finally of integrating output data indicative of such characterization from the plurality of applications in such fashion that errors in characterizations and inconsistencies between characterizations are minimized and the most comprehensive and accurate picture of the OF may be formed, has not been simply accomplished.
We refer to the process of providing an integrated characterization of output data from the plurality of analytical applications as “optimization,” a process that involves reconciling and/or minimizing errors among application outputs (which may consist of partial or entire approximate characterizations of the reservoir). In the past, when inconsistent characterization-related data was obtained from different analytic applications, the inconsistencies were not always readily resolved. Often, the only resolution that could be achieved was a human expert's choice among the inconsistent or disharmonious outputs, or by labor-intensive adjustment of incompatible types of data associated with each application, and feeding such adjusted data into a further processing step. The prior art has not contained a satisfactory system and method for creating and managing an automated workflow process to integrate many analytic computer applications and their handling, processing, and output of data relative to a reservoir in such fashion that: (a) data handling is largely automated; (b) disparate analytic applications are integrated or “wrapped” in a common user interface, which may be made remotely available; (c) workflow or processing hierarchies among the applications may be adjusted readily; (d) characterization data from the multiple applications is optimized, on an automated b

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