Details of Award
NERC Reference : NE/J006483/1
Active reservoir management for improved hydrocarbon recovery
Grant Award
- Principal Investigator:
- Professor IG Main, University of Edinburgh, Sch of Geosciences
- Grant held at:
- University of Edinburgh, Sch of Geosciences
- Science Area:
- None
- Overall Classification:
- Earth
- ENRIs:
- None
- Science Topics:
- Complexity Science
- Carbon Capture & Storage
- Earth Engineering
- Earth Resources
- Statistics & Appl. Probability
- Abstract:
- Hydrocarbon extraction for energy supply, or injection of CO2 to mitigate climate change, both require a detailed knowledge of the structure of underground reservoirs, and how they evolve in response to engineering decisions (when and where to inject or extract, how fast etc.). In this project we will develop a commercial version of a new statistical reservoir analysis technique discovered during a NERC grant as an aid to understanding and engineering such reservoirs. The new model is a way of extracting information directly from flow rate data already recorded at injector or producer wells without significantly adding to the cost of acquiring the data. It has proven successful in a number of field trials as a scientific concept, but it has been harder to prove commercial value without a version that could be run in trials by a practitioner. This project will provide such a platform, engage with potential end-users to make it as fit-for-purpose in its design, and extend the range of applications to a wider range of operational and commercial problems. The method was developed initially as a means of calibrating the response of faults and fractures to fluid injection and withdrawal. Faults and fractures provide key barriers or pathways to fluid flow underground, and their response is critical in determining extraction rates of oil and gas and the long-term integrity of underground CO2 storage sites. At present the method can (1) identify if a geo-mechanical response exists (so that more costly full-scale geo-mechanical modelling exercise can be justified where necessary), (2) identify which mapped or unmapped major fault structures are dominating this response, (3) identify changes in this response in time-lapse mode. A recent Market Research Report funded by a NERC pathfinder grant has (a) confirmed significant user interest in applying the method and in participating in early field trials and (b) highlighted the priority areas for potential applications in enhanced recovery of oil and gas. Accordingly, the major deliverable of this project will be a free-standing desktop tool to enable users to apply our technique to these problems on specific test cases where conventional analyses have proven insufficient, allowing the market to decide on its utility. Initial functionality will be based on the priority areas identified by the market research. The technology is based on establishing a multivariate regression model to forecast oil and gas production rates from past injection and production data. It provides a low-cost, optimised targeted search for the relevant well pairs that respond to each other, and quantifies the strength of the correlation. The scientific concept has been proven in a number of research articles and test cases, and in an independently-refereed, 'blind test' forecast of data not available to our team. End users will benefit primarily from having independent access to the technology, and being able to condition the functionality of the tool after the project in an explicitly commercial environment, particularly early adopters. The tool will add an independent constraint to current reservoir models used to optimise the extraction of oil and gas, at little extra cost compared to acquiring the data or carrying out a conventional reservoir model. They will be able to evaluate the commercial value in the applications identified above, and to extend the range to new ones.
- NERC Reference:
- NE/J006483/1
- Grant Stage:
- Completed
- Scheme:
- Follow on Fund (FEC)
- Grant Status:
- Closed
- Programme:
- Follow on Fund
This grant award has a total value of £117,359
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DI - Staff | DA - Estate Costs | DI - T&S | DA - Other Directly Allocated |
|---|---|---|---|---|---|---|
| £18,199 | £29,069 | £7,377 | £41,859 | £14,708 | £5,328 | £819 |
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