Ampomah, W. (Petroleum Recovery Research Center) | Balch, R. S. (Petroleum Recovery Research Center) | Grigg, R. B. (Petroleum Recovery Research Center) | Will, R. (Schlumberger Carbon Services) | Dai, Z. (Los Alamos National Laboratory) | White, M. D. (Pacific Northwest National Laboratory)
The Pennsylvanian–age Morrow sandstone within the Farnsworth field unit of the Anadarko basin presents an opportunity for CO2 enhanced oil recovery (EOR) and sequestration (CCUS). At Farnsworth, Chaparral Energy's EOR project injects anthropogenic CO2 from nearby fertilizer and ethanol plants into the Morrow Formation. Field development initiated in 1955 and CO 2injection started December 2010. The Southwest Regional Partnership on Carbon Sequestration (SWP) is using this project to monitor CO2 injection and movement in the field to determine CO2 storage potential in CO2-EOR projects.
This paper presents a field scale compositional reservoir flow modeling study in the Farnsworth Unit. The performance history of the CO2 flood and production strategies have been investigated for optimizing oil and CO2 storage. A high resolution geocellular model constructed based on the field geophysical, geological and engineering data acquired from the unit. An initial history match of primary and secondary recovery was conducted to set a basis for CO2 flood study. The performance of the current CO 2miscible flood patterns were subsequently calibrated to the history data. Several prediction models were constructed including water alternating gas (WAG), and infill drilling using the current active and newly proposed flood patterns.
A consistent WAG showed a highly probable way of ensuring maximum oil production and storage of CO2 within the Morrow formation.
The production response to the CO2 flooding is very impressive with a high percentage of oil production attributed to CO2 injection. Oil production increasingly exceeded the original project performance anticipated. More importantly, a large volume of injected CO2 has been sequestered within the Morrow Formation.
The reservoir modeling study provides valuable insights for optimizing oil production and CO2 storage within the Farnsworth Unit. The results will serve as a benchmark for future CO2–EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.
Given limited CO2 supply, operational constraints, and pattern specific reservoir performance, WAG schedule can be customized such that NPV or other metrics are optimized. Depending on the WAG schedule, recovery can fluctuate between 5–15% at the pattern scale due to reservoir heterogeneity causing variations in sweep efficiency. An analytical method was developed to optimize WAG schedules that couples traditional reservoir modeling and simulation with machine learning, enabling the discovery of optimal WAG schedules that increase recovery at the pattern level. A history-matched reservoir model of Chaparral Energy's Farnsworth Field, Ochiltree County, TX was sampled intelligently to perform predictive reservoir flow simulations and artificially build an intelligent reservoir model that samples a broad range of possible WAG scenarios for optimization. The intelligent model generates the next "best" sample to investigate in the numerical simulator and converges on the optima, quickly reducing the number of runs investigated. Results in this paper demonstrate that there can be significant improvements in net present value as well as net utilization rates of CO2 using this analytical technique. The WAG design generated by the intelligent reservoir model should be deployed in the field in early 2016 for validation. It is intended that the intelligent reservoir model will be updated on a regular basis as injection and production data is obtained. This effort represents the beginning of a paradigm shift in the application of modeling and simulation tools for significant improvements in field production operations.
With the synergy of horizontal drilling and hydraulic fracturing techniques, commercial production of Unconventional Liquid Reservoirs (ULR) has been successfully demonstrated. Due to the low recovery factor of these reservoirs, it is inevitable that Enhanced Oil Recovery (EOR) will ensue. Experimental results have shown promising oil recovery potential using CO2. This study investigates oil production mechanisms from the matrix into the fracture by simulating two laboratory experiments as well as several field-scale studies, and evaluates the potential of using CO2 huff-n-puff process to enhance the oil recovery in ULR with nano-Darcy range matrix permeability in complex natural fracture networks.
This study fully explores mechanisms contributing to the oil recovery with numerical modeling of experimental work, and provides a systematic investigation of the effects of various parameters on oil recovery. The core scale modeling utilizes two methods of determining properties that are used to construct 3D heterogeneous models. The findings are then upscaled to the field scale where both simple and complex fractures in a single stage are modeled. The effects of reservoir properties and operational parameters on oil recovery are then investigated. In addition, this study is the first to present simulation results of CO2 huff-n-puff using complex fracture networks which are generated from microseismic-constraint stochastic models.
Diffusion is proven to be the dominant oil recovery mechanism at the laboratory scale. However, the field-scale reservoir simulation indicates diffusion is negligible compared to the well-known mechanisms accompanying multi-contact miscibility. This includes swelling, viscosity reduction, and gas expansion in the matrix. Overall, the CO2 huff-n-puff process was found to be beneficial in both models in terms of enhancing the ultimate oil recovery in ULR.
There is considerable and timely interest in oil and condensate production from liquid-rich regions, placing emphasis on the ability to predict the behavior of gas condensate bank developments and saturation dynamics in shale gas reservoirs. As the pressure in the near-wellbore region drops below the dew-point, liquid droplets are formed and tend to be trapped in small pores. It has been suggested that the injection of CO2 into shale gas reservoirs can be a feasible option to enhance recovery of natural gas and valuable condensate oil, while at the same time sequestering CO2 underground. This work develops simulation capabilities to understand and predict complex transport processes and phase behavior in these reservoirs for efficient and environmentally friendly production management.
Although liquid-rich shale plays are economically producible, existing simulation techniques fail to include many of the production phenomena associated with the fluid system that consists of multiple gas species or phases. In this work, we develop a multicomponent compositional simulator for the modeling of gas-condensate shale reservoirs with complex fracture systems. Related storage and transport mechanisms such as multicomponent apparent permeability (MAP), sorption and molecular diffusion are considered. In order to accurately capture the complicated phase behavior of the multiphase fluids, an equation of State (EOS) based phase package is incorporated into the simulator. Due to the large capillary pressure that exists in the nanopores of ultra-tight shale matrix, the phase package considers the effect of capillary pressure on phase equilibrium calculations. A modified negative-flash algorithm that combines Newton's method and successive substitution iteration (SSI) is used for phase stability analysis under the effect of capillary pressure between oil and gas phases.
In addition, a lower-dimensional discrete fracture and matrix (DFM) model is implemented. The DFM model is based on unstructured gridding, and can accurately and efficiently handle the non-ideal geometries of hydraulic fracture in stimulated unconventional formation. Optimized local grid refinement (LGR) is employed to capture the extremely sharp potential gradient and saturation dynamics in the ultra-tight matrix around fracture.
We apply the developed simulator to study the combined effects of capillary pressure and multicomponent storage and transport mechanisms that are closely associated with the phase behavior and hydrocarbon recovery in gas-condensate shale reservoirs. We present preliminary simulation studies to show the applicability of CO2 huff-n-puff for the purpose of enhanced hydrocarbons recovery. Several design components such as the number of cycles and the length of injection period in the huff-n-puff process are also briefly investigated.
The Green River, Utah holds the world's greatest oil shale resources. However, the hydrocarbon, which is namely kerogen, extraction from shales is limited due to environmental and technical challenges. In this study, we investigated the effectiveness of the combustion process for shale oil extraction. Samples collected from the Green River formation were first characterized by X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). Then, series of dry combustion tests were conducted at different heating rates and wet combustion tests by water addition. The combustion efficiency was enhanced by mixing oil shale samples with an iron based catalyst. The effectiveness of dry, wet, and catalyst added combustion processes was examined by the thermal decomposition temperature of kerogen. Because the conventional oil shale extraction methods are pyrolysis (retorting) and steaming, the same experiments were conducted also under nitrogen injection to mimic retorting. It has been observed that the combustion process is a more efficient method for the extraction of kerogen from oil shale than the conventional techniques. The addition of water and catalyst to combustion has been found to lower the required temperature for kerogen decomposition for lower heating rate. This study provides insight for the optimization of the thermal methods for the kerogen extraction.
Production from liquid-rich shale has become an important contributor to domestic production in the United States, but recovery factors are low. Enhanced Oil Recovery (EOR) methods require injectivity and interwell communication on reasonable time scales. We conduct a feasibility study for the application of recycled lean gas injection to displace reservoir fluids between zipper fracs in liquid-rich shales.
Using new analytical solutions to the Diffusivity equation for arbitrarily-oriented line sources/sinks plus superposition, we analyze the time for inter-fracture communication development, i.e. interference, and productivity index for both classical bi-wing fractures in a zipper configuration and complex fracture networks. We are able to map both pressure and pressure temporal derivative as a function of time and space for production and/or injection from parallel motherbores under the infinite conductivity wellbore and fracture assumption. The infinite conductivity assumption could be later relaxed for more general cases.
We couch the results in terms of geometrical spacing requirement for both horizontal wells and stimulation treatments to achieve reasonable time frames for inter-fracture communication and sweep for parameters typical of various shale plays. We further analyze whether spacing currently considered for primary production is sufficient for direct implementation of EOR or if current practice should be modified with EOR in the field development plan.