Through its core research and development program administered by the National Energy Technology Laboratory (NETL), the U.S. Department of Energy (DOE) emphasizes monitoring, verification, and accounting (MVA), as well as computer simulation and risk assessment, of possible carbon dioxide (CO2) leakage at CO2 geologic storage sites. MVA efforts focus on the development and deployment of technologies that can provide an accurate accounting of stored CO2, with a high level of confidence that the CO2 will remain stored underground permanently. Effective application of these MVA technologies will ensure the safety of geologic storage projects with respect to both human health and the environment, and can provide the basis for establishing carbon credit trading markets for geologically storing CO2. The new technology is based on the concept of "smart fields," which is rapidly gaining support and popularity in the oil and gas industry. Smart fields integrate digital information technology with the latest monitoring techniques to provide continuous knowledge and control of reservoir operations and processes. Under this concept, hundreds of millions of dollars have been invested to successfully develop highly sensitive PDGs that are capable of operating in harsh environments for long periods. The PDGs collect and transmit high-frequency data streams in real time to remote control centers to be analyzed and used for reservoir management. The project team will use the pattern recognition power of state-of-the-art Artificial Intelligence and Data Mining (AI&DM) technology to develop a methodology, residing in a computer program, to recognize patterns from simulated realistic pressure data acquired from PDGs located within the reservoir model (Figure 1). This software will be capable of, but not limited to, locating point sources within a reservoir from which CO2 is leaking based on changes in pressure data. The methodology will autonomously cleanse and summarize raw data collected from in-situ pressure gauges, to prepare the data for processing and analysis. Upon completion, the methodology will be validated by its ability to accurately identify the location of simulated leakage points in a model of an existing heterogeneous reservoir. Once the approximate location of potential CO2 leakage is identified, the information will be communicated via e-mails, text messages, or other means to those performing "at" or "near" surface monitoring location for more precise detection and analysis. The main objective of this project is to develop the next generation of intelligent software that is able to take maximum advantage of the data collected by PDGs to continuously and autonomously monitor and verify CO2 storage in geologic formations as part of the effort to assure CO2 storage permanence in the subsurface. Further, the project team will investigate the feasibility of using this technology to monitor the growth and advancement of the CO2 plume during the injection process.
It will be necessary to improve existing monitoring technologies, develop novel systems, and protocols to satisfy regulations to track the fate of subsurface CO2 and quantify any emissions from reservoirs. The Carbon Storage Program is sponsoring the development of technologies and protocols by 2020 that are broadly applicable in different geologic storage classes and have sufficient accuracy to account for greater than 99 percent of all injected CO2. If necessary, the tools will support project developers to help quantify emissions from carbon capture, utilization, and storage (CCUS) projects in the unlikely event that CO2 migrates out of the injection zone. Finally, coupled with our increased understanding of these systems and reservoir models, MVA tools will help in the development of one of DOE’s goals to quantify storage capacity within ± 30 percent accuracy. Successful performance of this project will improve the understanding of factors affecting CO2 storage permanence and capacity, and increase confidence that CO2 placed in geologic formations is accurately tracked and that any leakage is detected and quickly treated. Results of the project are expected to be broadly applicable to a variety of geologic storage technologies and projects seeking to model potential CO2 leakage from geologic formations.
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