(206f) Field Testing of Emerging Techniques for Active Management and Monitoring of Commercial CO2 Storage | AIChE

(206f) Field Testing of Emerging Techniques for Active Management and Monitoring of Commercial CO2 Storage

Authors 

Bosshart, N. - Presenter, University of North Dakota
Hamling, J. A., University of North Dakota
Klapperich, R. J., University of North Dakota
Barajas-Olalde, C., University of North Dakota
Burnison, S., University of North Dakota
The Energy & Environmental Research Center (EERC) is partnering with the U.S. Department of Energy (DOE) National Energy Technology Laboratory and project partners to advance techniques that could benefit the active management and monitoring of commercial CO2 enhanced oil recovery (EOR) and geologic CO2 storage projects.

Because of a host of technical, social, regulatory, and economic factors, techniques that result in more compact and efficient CO2 storage in geologic formations are desirable. Results of several modeling studies indicate that active reservoir management (ARM) using brine extraction can reduce stress on sealing formations, geo-steer injected fluids and pressure plumes, divert pressure or fluids from potential leakage pathways or sensitive areas, reduce area of review, and improve geologic CO2 storage injectivity, capacity and efficiency. The EERC is validating these concepts through a well-designed field test being implemented at an active saltwater disposal (SWD) site that serves as a proxy for geologic CO2 storage. Simultaneous injection and extraction of brine using the existing SWD wells and a newly installed brine extraction well, combined with a monitoring program and reservoir simulation, are being used to evaluate the ARM scenarios being tested. As a proxy to commercial-scale geologic CO2 storage, the SWD site injects the equivalent of a quarter million tons of CO2/year on a volumetric basis which provides an established fluid and pressure plume that ARM performance can be validated against.

The monitoring program includes a time lapse borehole-to-surface electromagnetic (BSEM) survey, which is being conducted as a means of imaging changes in resistivity within the test formation. Brine injected at the site is displaced native saline formation water, creating a resistivity “plume” that can be measured by the BSEM survey. A baseline survey was acquired in the fall of 2018, and a repeat survey will be collected at the end of the field test. The baseline survey is being used to characterize site geology and identify the current distribution of the resistivity plume. The repeat survey will be used to validate reservoir simulations of ARM performance by measuring changes to the resistivity plume as a result of the field test.

The scalable, automated, semipermanent seismic array (SASSA) project led and managed by the EERC was a 3-year proof-of-concept study to evaluate and demonstrate an innovative application of the seismic method. By using a sparse surface array of nodal seismic sensors paired with a single, remotely operated active seismic source at a fixed location, strategically chosen reservoir reflection points were monitored for time-lapse changes that indicated CO2 saturation changes in the reservoir at those locations, thus monitoring the movement of the saturation front. The application differs from the normal paradigm of collecting a spatially dense data set to produce an image. Instead, standard time-lapse processing and innovative displays of incremental monitor trace data for individual receiver locations were analyzed for signal character changes that could be attributed to the passing of a CO2 saturation front or, possibly, changes in reservoir pressure. Monitoring was done in a low-impact, cost-effective manner, remotely, with the future intention of automating as many of the processes as possible.

Data collection occurred over the course of 1 year at an oil field undergoing CO2 injection for EOR and focused on four overlapping “five-spot” EOR injector–producer patterns. Selection, procurement, configuration, installation, and testing of project equipment and collection of five baseline data sets were completed in advance of CO2 injection within the study area. Weekly remote data collection produced 41 incremental time-lapse records for each of the 96 nodes.

CO2 injection data and the reservoir simulation results showed that saturation distributions in the study area progressed in a manner that only a subset of the 96 node midpoints could be expected to show character changes due to the presence of CO2. Data from twenty-six nodes were selected for in-depth analysis. The data sets were affected by several types of seismic noise which presented processing and interpretation challenges. Weather and the cultural noise associated with an active oil field were the most challenging because of their variability.

Interpretation results were encouraging, but mixed. Several nodes showed seismic reflection character changes indicative of the presence of CO2, while other nodes with corresponding reflection points where no CO2 was expected showed no effect. However, several nodes showed ambiguous interpretation because of poor signal-to-noise ratios. Validation methods from reservoir simulations and a time-lapse 2-D line acquired through the middle of the study area helped the interpretation but did not fully remove ambiguity.

A second iteration of the project is now under way in a different part of the field and directly addresses over twenty lessons learned during the proof-of-concept study. In particular, two powerful surface orbital vibrator sources that output 10 tons of force each are addressing the signal-to-noise issue. Two fixed source locations provide double the number of subsurface monitored points, and point locations have been chosen in conjunction with the field operator’s plans to minimize nodes that will not encounter CO2. The ultimate aim of the project is to evaluate whether SASSA technology can provide cost-effective monitoring of future CO2 injection projects.

The EERC has also explored the use of interferometric synthetic aperture radar (InSAR) as a monitor tool for CO2 EOR. SAR is an airborne or spaceborne radar system that first transmits microwave signals and then receives back the signals that are reflected, or backscattered, from Earth’s surface. InSAR is a technique for using high-resolution SAR images to generate high-quality digital terrain elevation maps with phase interferometry methods. Since InSAR can monitor ground deformation, it is possible to assess the impact of injecting CO2 into the reservoir at Earth’s surface.

InSAR data were acquired over a 370-km2 area that covered an oil field at various phases of EOR development. The Advanced Land Observation Satellite (ALOS) and COSMO-SkyMed (CSK) satellite system were used to acquire data between 2007 and 2011. ALOS acquired 21 sets of InSAR measurements every month from 2007 to 2011 but lost power 2 years before the start of CO2 injection at Bell Creek. CSK acquired measurements approximately every 16 days starting in 2015. The CKS data, which provide both higher frequency measurements, higher resolution data, longer wavelengths, and lower-noise levels, were used to investigate the applicability of INSaR measurements to monitor CO2 EOR floods in complex (e.g., seasonal snow cover, challenging topography, vegetation changes, etc.)

A processing technique called SqueeSAR was applied to CSK data to overcome the InSAR challenges associated with atmospheric effects and with the topography, agricultural activities, months of snow cover, and areas of pine forest of the Bell Creek Field. Strong correlations between fluid injection/production and surface elevation changes were observed in areas that corresponded to a compartmentalized distribution of geologic heterogeneities. Correlations between net fluid injection/production and small changes in the surface elevation were improved by removing low-frequency trends and applying time lag to the InSAR time series. Estimated reservoir pressure differences from geomechanical modeling and InSAR data inversion validated the observed correlations.

The work indicates that InSAR techniques may provide a low-cost, low-impact means of better understanding CO2 EOR pattern performance and reservoir heterogeneities in challenging surface environments.