Low primary recovery percentages from unconventional reservoirs have long motivated interest in Enhanced Oil Recovery (EOR) for these reservoirs, resulting in numerous simulation studies and injection pilots. However, performance from injections pilots has typically been disappointing compared to the simulations, suggesting that reservoir permeability and heterogeneity are not adequately described in the reservoir simulation models. In this study, a simulation and history-matching approach was used to quantify the permeability matrix over a six-section, nine-well area. Twelve years of production data were history-matched, using a combination of pressure-dependent permeability and enhanced permeability to represent natural fractures or other high-permeability features. Also, the performance of a failed injection pilot was history-matched to determine the level of reservoir heterogeneity needed to explain the pilot failure. Based on this study, a reservoir description capable of matching twelve years of production and injection history has been developed. Formation properties in the high-permeability streaks capable of causing the disappointing injection pilot performance have been quantified. Recovery has been forecast to depletion, and EOR under hydrocarbon gas injection has been forecast for a variety of scenarios. Optimal operating strategies and recommendations for technology development to mitigate early breakthrough are made. Realistic cost estimates were made for each scenario, and economics were run for each recovery method. These results give insight into the economic potential of enhanced oil recovery in the Elm Coulee Bakken formation. Recommendations for favorable tax treatment and scheduling of expenses/investments are made. Developing the permeability matrix using the history matching approach is a novel and versatile way of quantifying unconventional reservoir properties. However, it is important to match both injection and production data, since the permeability vector appears to have pressure-dependent effects. The effect of controlling injection thief zones by controlling local wellbore outflow is quantified, and a need for in situ permeability modification of fracture thief zones has been determined.
Unconventional reservoirs produce large volumes of oil; however, recovery factors are low. While enhanced oil recovery (EOR) with cyclic gas injection can increase recovery factors in unconventional reservoirs, the mechanisms responsible for additional recovery are not well understood. We examined cyclic gas injection recovery mechanisms in unconventional reservoirs including oil swelling, viscosity reduction, vaporization, and pressure support using a numerical flow model as functions of reservoir fluid gas–oil ratio (GOR), and we conducted a sensitivity analysis of the mechanisms to reservoir properties and injection conditions. All mechanisms studied contributed to the additional recovery, but their significance varied with GOR. Pressure support provides a small response for all fluid types. Vaporization plays a role for all fluids but is most important for gas condensate reservoirs. Oil swelling impacts low-GOR oils but diminishes for higher-GOR oil. Viscosity reduction plays a minor role for low-GOR cases. As matrix permeability and fracture surface area increase, the importance of gas injection decreases because of the increased primary oil production. Changes to gas injection conditions that increase injection maturity (longer injection times, higher injection rates, and smaller fracture areas) result in more free gas and, for these cases, vaporization becomes important. Recovery mechanisms for cyclic gas injection are now better understood and can be adapted to varying conditions within unconventional plays, resulting in better EOR designs and improved recovery.
The use of artificial neural networks (ANN) for reservoir analysis now makes it possible to predict important reservoir properties from combinations of data such as well logs, production data, seismic data, etc. In this work, an ANN was combined with a geostatistical linear estimation algorithm in a technique called the hybrid approach, which was used to enhance sparse data to include in a reservoir simulation model with the goal of reducing history matching time. The case study field, Fort Collins Field, is situated on the N-S anticline on the western edge of the Denver Basin in Colorado. The available porosity and permeability data needed to build a reservoir simulation model are old and sparse. Available well logs and cores were used as inputs to the hybrid model. This model was then used to predict porosity and permeability for the reservoir and these values were then included in a reservoir simulation model. To evaluate the hybrid approach, the reservoir simulation model was history matched with the case study historical production data and compared to a model with average data. The result confirms that the hybrid approach history matched better and faster compared to the simple averaging-technique. The history match results from both methods were compared based on the percentage error. This unique approach will benefit older fields with sparse data.
Unconventional reservoirs hold vast amounts of untapped hydrocarbon resources; however, given current production capabilities and our understanding of unconventional reservoir production mechanisms only 5% to 10% of these hydrocarbons are typically recovered. The ability to recover additional hydrocarbons from unconventional reservoirs is dependent on an improved understanding of the production mechanisms which are a function of the complex lithology and reservoir fluid systems, and the interactions between these systems. The lithology and fluid systems present in most unconventional reservoirs result in production from several scale-dependent fluid flow and storage systems, or depletion systems, that combine to contribute to the total production. These depletion systems can include matrix level features defined by pore size, natural fracture systems within the matrix, and hydraulic fractures in addition to the traditional depletion systems defined by stacked pay. The fluid phase behavior within these systems also has a scale dependence that must be taken into consideration. As a result, the individual systems tend to deplete at different rates. The purpose of this work is to describe the production mechanisms in terms of the lithology and reservoir fluid interactions. By using numerical simulation to systematically isolate production from individual depletion systems, the role and significance of each system is quantified. A numerical model was developed to simulate the contributions to total hydrocarbon production from multiple depletion systems. Fluid tracers were placed within each depletion system to isolate the individual system production. The results show the stage of production when each depletion system is active and the associated hydrocarbon volumes. For example, the hydraulic fracture system provides most of the initial production, but contribution from the matrix and natural fractures quickly overtakes it. Composite production curves were developed by combining the simulated production contributions from each depletion system, highlighting the influence the different systems have on the total production. This paper provides insights into the production contributions from multiple depletion systems found in many unconventional reservoirs. Understanding the roles that the different depletion systems play on production will lead to better well spacing, reserve estimates, and improved reservoir production practices including enhanced oil recovery methods that may be optimized to target the most promising aspects of the reservoir.
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