Master of Science / Department of Geology / Abdelmoneam Raef / In this study, laboratory measurements of ultrasonic frequency P- and S-wave velocities were collected and analyzed from two sets of cores. The first set is from a near surface study in southeastern Kansas, and the second set was from the deep subsurface and obtained from a newly drilled well (Wellington KGS 1-32) in Sumner County, KS. Ultrasonic velocities acquired from the second set of cores were then compared with in situ sonic and dipole sonic frequencies of P- and S-waves from well logs. Well log data, core data, and ultrasonic velocity measurements were integrated for Gassmann fluid replacement modeling. The understanding of the velocity and elastic moduli variations at ultrasonic frequencies, along with the comparison of well log velocities can potentially provide improved understanding to establish a beneficial calibration relationship. It could also allow for estimation of shear wave velocities for wells lacking dipole sonic log data. The ability to utilize cost-effective ultrasonic measurements of velocities and elastic moduli in the laboratory, for fluid replacement modeling (Gassmann) in CO[subscript]2-sequestration, as well as, enhanced oil recovery (EOR) projects, would be a significant advance. Potential alternative use of ultrasonic velocities for determining the effects of fluid replacement using Gassmann modeling, when log data is lacking, is an ongoing effort. In this study, the fluid replacement modeling is executed based on sonic and dipole sonic P- and S-wave velocities and compared with results from theoretical modeling. The significance of this work lies in the potential of establishing a calibration relationship for the representative lithofacies of the carbon geosequestration target zone of the Wellington KGS 1-32 well in Sumner County, and enabling the use of ultrasonic measurements of body wave velocities and elastic moduli in Gassmann fluid replacement modeling. This work, when integrated with continuing effort in mapping lithofacies of the Arbuckle and Mississippian groups, would potentially be of great importance to fluid flow simulation efforts and time-lapse seismic monitoring. This study will utilize Gassmann modeling and a range of measurements and data, which include: well logs and ultrasonic laboratory P- and S-wave measurements and core analysis data.

Master of Science / Department of Geology / Abdelmoneam Raef / Amid increasing interest in geological sequestration of carbon dioxide (CO2), detailed rock formation characterization has emerged as priority to ensure successful sequestration. Utilizing recent advances in the field of 3D seismic attributes analysis, offers improved opportunities to provide more details when characterizing reservoir formations. In this study, several post-stack seismic attributes integrated with seismic modeling for highlighting critical structural elements and petrophysical facies variation of rock formations at Wellington and Anson-Bates fields, Sumner County, Kansas. A newly acquired 3D Seismic data set and several geophysical well logs are also used to achieve the objectives of this study. Results sought in this study are potentially important for understanding pathways for CO2 to migrate along. Seismic amplitude, coherency, and most negative curvature attributes were used to characterize the subsurface for structural effects on the rock formations of interest. These attributes detect multiple anomaly features that can be interpreted as small throw faults. However, in this study, there is a larger anomalous feature associated with the Mississippian formation that can be interpreted as a small throw fault or incised channel sand. Determining which of the two is very important for flow simulation models to be more exact. Modeling of the seismic was undertaken to help in the interpretation of the Mississippian amplitude anomaly. An artificial neural network, based on well log porosity cross-plots and three seismic attributes, was trained and implemented to yield a seismic petrophysical facies map. The neural network was trained using three volume seismic waveform attributes along with three wells with difference in well log porosity. A reworked lithofacies along small throw faults has been revealed based on comparing the seismic structural attributes and the seismic petrophysical facies. Arbuckle formation characterization was successful to a certain degree. Structural attributes showed multiple faults in the northern half of the survey. These faults are in agreement with known structure in the area associated with the Nemaha uplift. Further characterization of the Arbuckle was hindered by the lack of well data. This study emphasizes the need for greater attention to small-scale features when embarking upon characterization of a reservoir for CO2 based geosequestration.