Induced Seismicity: Modeling the Fort Worth Basin
For two decades, large amounts of water have been disposed of in the faulted and karsted carbonate formation in the Fort Worth Basin (North Texas). The disposed water comes from water that has been injected into the overlying Barnett Shale to enhance gas recovery. As a result of this disposal, earthquakes have been observed in the region since 2012. The earthquakes occur in the much deeper underlying crystal granite basement, lag in time, and are laterally far from areas with peak water disposal.
In basin-scale numerical simulations, available data is severely limited and unevenly distributed, and extensive sensitivity analysis has been carried out to estimate numerous unknown parameters for the formation. Jean-Philippe Nicot and I have come up with a thorough and detailed numerical flow model. Basin-scale pore pressure evolutions are evaluated through space and time, and predictions are provided under different disposal scenarios.
This is a fundamental step in evaluating the potential for fault activation on behalf of the larger TexNet-CISR project. The results will aid in collaborative research to address the issue of induced seismicity in the region.
Enhanced Modelling of Improved Oil Recovery from Mature Texas Reservoirs
The STARR program's Improved Oil Recovery Group helps Texas operators increase production by optimizing water floods and CO2 enhanced recovery (EOR) operations. One of the largest oil reserves in Texas lies in remnant hydrocarbons from mature oil fields. This oil could be accessed by a variety of improved oil recovery techniques including water flooding, CO2 flooding, CO2 foam, and polymer flooding.
Our main interest is in the Permian Basin, but we are also developing projects in the Texas Gulf Coast. Our work integrates careful geologic logging of core data with measurement of petrophysical properties, seismic data analysis, and interpretation of wireline logs to build 3D geological models. Recent research projects have included:
- the nature and origin of residual oil zones (ROZ) associated with San Andres reservoirs,
- the geology and geochemistry of the Seminole Field reservoir in Gaines County,
- analysis of net present value for CO2 foam-based EOR.
During this research, I have developed a new model for the origins of ROZs. This changes the whole concept of how to explore for economically viable zones.
Future projects include:
- leading a team optimizing water floods for small operators,
- developing methods to optimize the economic value of CO2 floods,
- analyzing the mechanisms involved in near-miscible CO2 flooding,
- assessing the effects of complex geometries of multi-modal pore system on capillary pressure versus saturation relationships and relative permeability,
- using machine learning to take detailed petrophysical measurements from cored intervals to provide more accurate parameter estimates from wireline-log data for un-cored intervals.
Male, F. and Duncan, I.J., 2020. Lessons for machine learning from the analysis of porosity-permeability transforms for carbonate reservoirs: Journal of Petroleum Science and Engineering, 106825, doi:10.1016/j.petrol.2019.106825.
Ren, B. and Duncan, I.J., 2019. Reservoir simulation of carbon storage associated with CO2 EOR in residual oil zones, San Andres formation of West Texas, Permian Basin, USA: Energy, 167, pp. 391–401, doi:10.1016/j.energy.2018.11.007.
Ren, B. and Duncan, I., 2019. Modeling oil saturation evolution in residual oil zones: Implications for CO2 EOR and sequestration: Journal of Petroleum Science and Engineering, 177, pp. 528–539.
Male, F., Aiken, C. and Duncan, I.J., 2018, Using Data Analytics to Assess the Impact of Technology Change on Production Forecasting. In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers.
Meng, M., Fan, T., Duncan, I.J., Yin, S., Gao, Z., Jiang, L., Yu, C. and Jiang, L., 2018. Characterization of carbonate microfacies and reservoir pore types based on Formation MicroImager logging: A case study from the Ordovician in the Tahe Oilfield, Tarim Basin, China: Interpretation, 6(1), pp. T71–T82, doi:10.1190/INT-2017-0043.1.