Open Access
Kulga, Ihsan Burak
Graduate Program:
Energy and Mineral Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
June 09, 2014
Committee Members:
  • Turgay Ertekin, Dissertation Advisor
  • Sarma V Pisupati, Committee Member
  • Zhen Lei, Committee Member
  • Savas Yavuzkurt, Committee Member
  • numerical model
  • CO2 injection
  • shale gas
  • artificial neural network
  • stimulated reservoir volume
  • srv
  • ann
In this study, the possibility of industrial CO2 storage in shale gas reservoirs is investigated numerically by using one of the most advanced computational simulators in oil and gas industry, PSU-SHALECOMP, which is a compositional dual porosity, dual permeability, multi-phase reservoir simulator. A computationally inexpensive “stimulated reservoir volume” (SRV) model which has the ability to generate a similar behavior of an equivalent discrete fracture network model is defined and implemented. Three different commercial production profiles are history-matched by using the SRV approach effectively. It is re-proved that implementation of the horizontal borehole technology and hydraulic fracturing are the two most important factors that will increase the efficacy of methane production and carbon dioxide injection processes. It is observed that significantly large percentage of the produced gas originates from the fractured zone so as significantly large percentage of the injected gas will end up occupying the pore spaces in the fractured zone. Injection of carbon dioxide into undepleted shale gas reservoirs is not promising because of its ultra-tight permeability characteristics. Injection of carbon dioxide into shale gas reservoirs that have produced approximately 30\% of the initial gas in place is promising. It is observed that when 30\% of shale gas production is achieved, up to 70\% of the depleted gas volume is expected to be replaced by carbon dioxide. The storage capacity of the depleted shale gas reservoir can be increased by injecting carbon dioxide at a rather low rate. A low rate injection of carbon dioxide will increase its residence time in the flow domain increasing its chances for adsorption. If the SRV zones of the production and injection wells are not in direct communication, it is not expected to see carbon dioxide breakthrough at the producing well. It is also investigated that contribution of carbon dioxide in enhancing the shale gas recovery is negligible. The study includes developments of four artificial neural network tools that have different production of methane and injection of carbon dioxide constraints. These four forward tools can produce production and injection profiles of a given system within an error range of 3.83\% to 5.23\%. This part of the study also includes four additional artificial neural network tools that predicts wellbore design and hydraulic fracture characteristics within an error range of 8.24\% to 9.93\%.