[CCoE Notice] Dissertation Defense: Improved workflow for EUR prediction in Unconventional Reservoirs

[Grayson, Audrey A]

MS Dissertation Defense


Improved workflow for EUR prediction in Unconventional Reservoirs
Akash Sharma

Date: Thursday, December 3, 2015

Location: Room 123, Building 9, Energy Research Park, UH
Time: 10:30 am – 12:30 pm

Committee Chair: Dr. Konstantinos Kostarelos

Committee Members:
Dr. John Lee
Dr. Evgeny Chesnokov

ABSTRACT

Maximizing recovery of hydrocarbons from unconventional reservoirs poses a serious challenge as our understanding of these complex systems is still in a nascent stage. The behavior of shale formations is totally different from that of conventional sandstone/limestone formations due to which they do not work effectively with our existing models and methodologies.

Production forecasting is especially a complication as the degree of uncertainty increases immensely and there is lack of accuracy in the predictions. Furthermore, there isn’t sufficient history to correlate our findings and substantiate models in shale formations. The degree of heterogeneity in these reservoirs puts to question the use of data and results from other wells in shales.

Although multiple models have been created that can effectively model the production behavior of unconventional plays, by and large the oil and gas industry still relies on the older models. This is due to their comparative simplicity and better understanding with decades of being in use. The workflow developed aims to provide accuracy while developing an ease of access in using these more accurate models.

The study has also looked into Boundary-Influenced flow, the flow regime that is found between linear flow regime and Boundary Dominated flow regime. A few approaches to tackle this flow regime have been suggested and have been incorporated into the overall workflow.

The study deals with the task of verifying the work with various comparative analysis and validation procedures and delves into how this workflow contributes into the overall decision making process and assist the company in making more informed and better choices regarding field development and investment opportunities.
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