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Dr.Robert
Balch, Research
Group Head, e-mail: balch@prrc.nmt.edu Phone: 575-835-5305. Fax: 575-835-6031 |
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| New Mexico Pit Rules | ||||||
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With the adoption of new "Pit Rules" in July 2008, New Mexico's producers have experienced an increase in required compliance data required for pit applications which has dramatically affected both application preparation time and time for regulatory review of those applications. Since failure to include best possible and available data could increase exposure to environmental and financial risk, small producers have needed to divert critical personnel from regular tasks to the collection and presentation of compliance data.
The Petroleum Recovery Research Center at New Mexico Tech has been funded by the RPSEA Small Producer Program to create The New Mexico Pit Rule Mapping Portal which generates software and maps of potential site regulatory issues using government recommended data and should reduce time needed for evaluation, preparation and review of C-144 forms and attachments and allow better determination of optimal and allowed locations of pits and tanks with respect to current siting criteria. |
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| Oil and Gas Potential Analysis - Secretary of the Interior's Potash Area - SE New Mexico | ||||||
| This study combines to-date geologic understanding of the area with historic production data to make per-acre estimates of underdeveloped oil and gas reserves within the geologic boundaries of the main body of the Oil Potash Leasing Area, as defined by the New Mexico Oil Conservation Division Rule R-111-p. The purposes were twofold: First to provide a database and Geographic Information System which illustrates development potential utilizing existing oil and gas plays; and second to provide economic estimates of the total values of those resources and as royalty and tax revenues to federal, state, and local governments. | ||||||
| Data Mining Consortium | ||||||
| Advances in computer power and database management have led to the development of powerful algorithms for making proactive business decisions using large databases. This consortium actively pursues research to apply data mining to industry applications. A pilot project was performed which determined optimal completion techniques for San Juan basin Dakota wells which can decrease overall completion costs while optimizing potential recovery. For information on joining the consortium contact Robert Balch | ||||||
| Fuzzy Expert Exploration (FEE) Tool | ||||||
| Incomplete or sparse information on types of data such as geologic or formation characteristics introduces a high level of risk for oil exploration and development projects. Expert systems developed and used in several disciplines and industries have demonstrated beneficial results. A state-of-the-art exploration "expert" tool, relying on a computerized database and computer maps generated by neural networks, is being developed through the use of "fuzzy" logic, a relatively new mathematical treatment of imprecise or non-explicit parameters and values. Oil prospecting risk can be reduced with the use of a properly developed and validated "Fuzzy Expert Exploration (FEE) Tool. | ||||||
| Web-Based Database Management System(WDMS) | ||||||
| A dynamic web-accessible database for storing, managing, accessing, and analyzing data. This Brushy Canyon specific database has also been used in the development of heuristic fuzzy rules. The data available in WDMS includes well log sections and production data for Brushy Canyon wells. Zoom able maps of key regional attributes such as structure, porosity thickness, gravity and aeromagnetic data are also available. Data is downloadable in Microsoft access or Excel formats and advanced queries are possible by users with SQL experience. | ||||||
| Fuzzy Rank | ||||||
| There are a number of ways to select the best set of inputs to be used to form a regression for a particular output. Simply crossplotting each input against the output can give an indication of the quality of linear or multiple linear regression models that could be formed. In the development of an on line Expert system for oil prospecting we have encountered many non-linear or complex problems. To address this software was developed based on a single stage fuzzy-ranking algorithm to select inputs best suited for predicting the desired output. This global algorithm statistically determines how we ll a particular input could resolve a particular output with respect to any number of other inputs using fuzzy curve analysis. | ||||||
| Predict Online | ||||||
| PredictOnline is a web based implementation of a neural network conjugate gradient algorithm using the conjugate gradient algorithm. PredictOnline is in its 6th version and the most recent improvements include the removal of the java policy file. In the previous versions, a java policy file was needed on the user's computer to allow PredictOnline to access data via applets. Upload and download functions without java policy files have been developed using Java Server Pages. | ||||||