The Petra Nova Project is a commercial-scale post-combustion capture project at W.A. Parish Electric Generating Station from which CO2 is captured, transported and injected into the West Ranch oilfield where it boosts oil production. The project is a joint venture between NRG Energy, Inc. and JX Nippon Oil Exploration Limited. The project captures roughly 5,200 short tons of CO2 per day at full capacity with about 92% of the CO2 from the slip stream of flue gas processed. The Gulf Coast Carbon Center (GCCC) was involved in Phase 3: Demonstration and Monitoring to monitor, verify, and account for the sequestered CO2. At the end of this phase, the project had captured a total of nearly 4 million short tons of CO2. GCCC’s objectives as stated in the project description were to a) demonstrate the specified advanced technologies constructed during Phase 2 and b) monitor the injected CO2 at West Ranch to demonstrate technologies and protocols for monitoring verification, and accounting (MVA). The components of the monitoring are as follows: fluid flow modeling, mass balance accounting, pressure monitoring, geophysical logging, fluid sampling and analysis, characterization of underground sources of drinking water, and soil (vadose-zone) definition.
Fluid flow modeling
To determine the capacity of the subsurface to hold injected CO2, fluid flow modeling was conducted. By comparing subsurface response to model predictions, CO2 can be shown to stay within the targeted area.
By analyzing the most substantial risk of unexpected loss of CO2 to atmosphere— failure of well designs intended to isolate the subsurface zones from near surface zones—the scientists modeled well leakage scenarios to determine the above-zone pressure response to such leakage.
The first step in the modeling process was to build a static reservoir model, constructed from well logs so that the target sandstones and seals are defined. The model was then populated with rock type, porosity, and permeability by data collected on rock properties.
Fluid properties were then added to history match the production and pressure data to simulate activities within the field. The resulting dynamic numerical model contained water, oil, and gas properties, relative permeability data, as well as thermodynamic properties and injection and production volumes. The model was history-matched successfully with the field injection-production-pressure history.
Mass balance accounting
Mass balance accounting takes into account the amount of fluids injected, withdrawn, recycled, and lost during an operation—particularly when oil is produced and CO2 becomes trapped within the reservoir so that it is not recycled.
The GCCC’s method subtracts surface and subsurface losses compared to the captured CO2 injected into the subsurface. Injected CO2 was measured with flow meters at the capture plant and upstream of the recycle gas compressor. Gas composition was taken into account and corrected to include only CO2.
CO2 lost to surface equipment was also accounted for. Lost CO2 at the surface includes vapored gas released, blowdown releases, as well as other maintenance as well as unintended losses.
Under GCCC’s guidance, the project calculated a total of 3,609,924 short tons sequestered and 3,643,146 short tons of CO2 captured, meeting the Department of Energy’s target ratio of captured to stored.
Reservoir depth pressure changes are critical to monitoring that validates fluid flow models. Monitoring pressure shows that the magnitude and area of pressure elevation is as permitted, monitor fluid movement in the reservoir, and identify unintended vertical migration of fluids. Monitoring at the project collected data from above-zone monitoring wells, and in-zone monitoring wells equipped with bottom-hole pressure and temperature gauges. The above-zone pressure monitoring targets leakage detection.
The above-zone monitoring interval (AZMI) was determined by the following criteria: a permeable zone where fluid would migrate out of if possible and also hydrologic characteristics that would allow detection of the pressure signal.
Geophysical logging assessed the extent of pore volumes occupied by CO2 as EOR flooding continued. Pulsed neutron logs were collected before and after flooding then inverted to measure CO2 saturation. This data leads confirm no migration out of the intended zone.
Fluid sampling and analysis
The geochemistry of transported CO2, the brine in the in-zone and above-zones, and the gases in the head space of deep monitoring wells was characterized. These data can be used to create mixing lines such that a change in groundwater chemistry due to a hypothetical unintended migration of hydrocarbon any of the fluids from depth into groundwater can be recognized and attributed.
Characterization of underground sources of drinking water
Water chemistry of two near surface fresh water aquifers (USDW), was measured to define the current variability of the groundwater system. The shallow ground water system was complex with multiple contributions to the observed dissolved phases. This in turn was used which used to in reactive transport models to attribute changes in groundwater chemistry to contamination by fluids from depth, changing water chemistry.
Comparing the stable carbon isotopic composition of methane to the ratio of methane to ethane and propane was used as a method for recognizing deep sources, as well as strontium concentrations and isotopes in this setting.
Soil (vadose-zone) definition
To characterize the composition of soil gases, semi-permanent soil gas sampling chambers were installed. The models developed to attribute the cause of soil gas anomalies analyze the concentrations and isotopic compositions of naturally occurring soil gases and those caused by an unintended migration. Gas was collected in gas bags and analyzed for CO2, O2, N2, and CH4 as well as He, H2, CO, and higher hydrocarbons. A process-based approach developed by GCCC using the relationships between coexisting soil gases was used as well as radiocarbon and stable carbon isotopes to further assess any existing anomalies.
This was funded and managed by the U.S. DOE/NETL under award number DE-FE0003311.
Last Updated: October 27, 2020