Date of Award
August 2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Geology
First Advisor
William Gosnold
Abstract
This dissertation employed advanced seismic imaging techniques to present a comprehensive study on fracture network mapping from the Lodgepole Formation in McKenzie County, North Dakota. The research addresses the critical need for accurate fracture detection and characterization in complex carbonate formations, with a focus on geothermal energy applications. The study integrates multiple data sources, including 3D seismic surveys, well logs, core samples, and production data, to develop a robust methodology for fracture network analysis. A novel Multi-Objective Golden Eagle Optimization (MOGEO) algorithm was introduced, combining multiple seismic attributes to produce high-resolution fracture maps. The MOGEO algorithm demonstrates superior performance in fracture delineation compared to conventional methods while adhering to geological constraints. Petrophysical analysis reveals that the average porosity were valued of 25.5% and permeability ranging from 0.12 to 2.8 mD in the Lodgepole Formation. Geochemical analysis indicates hypersaline Ca-Na-Cl brines with total dissolved solids concentrations were ranged from 2,647 to 352,432 mg/L. Thermal characterization shows bottom-hole temperatures between 80°C and 120°C, with an average geothermal gradient of 47.4°C/km. A system dynamics model was developed to simulate the interplay between fracture networks, fluid flow, and geothermal energy production. The model demonstrates the critical role of fracture detection in sustainable geothermal operations and provides insights into potential optimization strategies. The research also revealed that the dominant fracture strike orientation aligns with the southeast-northwest direction when incorporating geomechanical analysis, which is consistent with the regional stress regime. This information provides valuable context for interpreting seismic attribute results and fracture network behavior prediction under changing stress conditions. The findings of this study have significant implications for geothermal energy development in carbonate reservoirs. The enhanced fracture detection capabilities offered by the MOGEO can lead to more accurate predictions on the pathways of fluid flow, optimization of well placement strategies, and improvement in geothermal reservoir management. This dissertation contributes to the field of subsurface characterization by providing a comprehensive framework for fracture network analysis in complex geological settings. The methodologies developed herein have the potential to significantly advance our ability to harness geothermal resources efficiently and sustainably, supporting the global transition to clean, renewable energy sources.
Recommended Citation
Alamooti, Moones, "Fracture Networks Mapping From Lodgepole Formation, McKenzie County, North Dakota Using Seismic Imaging" (2024). Theses and Dissertations. 6406.
https://commons.und.edu/theses/6406