Robert Balch

CO2 Accounting and Risk Analysis for CO2 Sequestration at Enhanced Oil Recovery Sites.

Using CO2 in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce sequestration costs in the absence of emissions policies that include incentives for carbon capture and storage. This study develops a multiscale statistical framework to perform CO2 accounting and risk analysis in an EOR environment at the Farnsworth Unit (FWU), Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil/gas-water flow and transport in the Morrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2/water injection/production rates, cumulative net CO2 storage, cumulative oil/gas productions, and CO2 breakthrough time. The median and confidence intervals are estimated for quantifying uncertainty ranges of the risk metrics. A response-surface-based economic model has been derived to calculate the CO2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO2 capture and operating expenses reduce, more realizations would be profitable. The results from this study provide valuable insights for understanding CO2 storage potential and the corresponding environmental and economic risks of commercial-scale CO2-sequestration in depleted reservoirs.

Collection, storage and application of human knowledge in expert system development

: Expert systems are programs that analyze data by mimicking the thought processes of an expert. Two expert systems were developed by the Reservoir Evaluation and Advanced Computational Techniques group to aid in oil prospecting for two New Mexico formations, leading to the development of a third customizable fuzzy expert system. Knowledge engineering is a major part of the development of these expert systems, in which expert knowledge is solicited, analyzed, converted to rules stored in a systems knowledge base, and used by the computer to produce expert judgment. Numerical versions of the rules are used to analyze data and produce an evaluation of the users prospect. In addition, the knowledge base preserves expert knowledge for future workers. This is especially important in the petroleum industry, as there is a cyclical trend in employment relating to the price of oil, retirements and people leaving and entering the industry.

The Fuzzy Expert Exploration Tool for the Delaware Basin: Development, testing and applications

The Delaware Fuzzy Expert Exploration Tool (FEE Tool) is an expert system designed to reduce exploration risk for the Lower Brushy Canyon formation of the Delaware Basin. The components of the Delaware FEE Tool include a knowledge base containing sets of rules developed through expert interviews, an answer base of numerical inputs to these rules, an inference engine that uses fuzzy logic to evaluate the rules with answer base or user-provided data, and a user interface where the user can work with input data and interpret the tools results. For each of 60,478,40-acre locations in the New Mexico portion of the Delaware Basin, the FEE Tool output includes a scaled quality estimate in the set {0, 1}, with a value of 0.65 or greater, indicating a low risk prospect. In testing, the quality estimates were found to be significantly higher at locations where recent successful wells were located. The Delaware FEE Tool was also used as a reserve estimation tool by relating the FEE Tool estimate at a known producing well to its total expected production. Then the FEE Tool estimates at undrilled locations were used to calculate a reserve estimate. Using this approach, the probable regional reserves were estimated to fall between 278 and 432 millionbbls.

A fuzzy expert system for oil prospecting in the Lower Brushy Canyon of SE New Mexico

This paper presents a fuzzy expert system, the fuzzy expert exploration tool (FEE tool), developed for oil prospecting in the Lower Brushy Canyon of SE New Mexico. It was developed using two types of rules, heuristic rules, generated directly from geophysical and geological databases, and expert rules developed through interviews with successful prospectors. Rules are applied in three categories, regional assessment, trap assessment, and formation assessment. The FEE tool uses a unique fuzzy inference method, and is available to users through the Internet using a Java capable Web browser. It is built on a three-tier model and is implemented using Java Applets and Java Servlets supported by Tomcat application server.

Producing GOR Used to Predict Permeability Distribution in a Tight Heterogeneous Reservoir

Production from tight reservoirs can yield flow pressures around the wellbores that are below the bubblepoint. The accumulation of free gas around the wellbores results in a rapid increase in the producing gas-oil ratio (GOR). This paper investigates the sensitivity of depletion-drive GOR to variations in permeability. A public domain, black oil simulator was modified to automatically estimate the permeability from GOR histories. The method presented in this paper is especially useful when interpretable pressure transient tests are not available and can be adapted to existing simulators without changing the core code. A multi-objective, simultaneous bisection algorithm was developed to provide automatic GOR history match and to predict permeability distributions. Following each iterative simulation run, the permeability-searching intervals for all of the wells were simultaneously reduced by half and the permeability distribution map was updated. The updated searching intervals are uniquely determined because the permeability-GOR correlation is monotonic. Usually a satisfactory match is obtained within 10 simulation runs, which is much more efficient than the gradient or stochastic methods typically used for an automatic history matching procedure. This method was applied to field data from the South Bisti Gallup Pool. Well communication tests have shown a strong permeability preference for a southwest-northeast orientation in the pools two tight pay zones. The automatic GOR match was applied to the 14-year depletion history of 52 wells. First, the ratio of K g /K o was estimated from the total field GOR match. Then, the local variation of permeability was determined according to the GOR history of the wells. Two perpendicular- oriented permeability distributions were obtained. This new method should be valuable for other low permeability reservoirs.