Energy Policy Act of 2005 (Ultra-deepwater and Unconventional Resources Program)
Optimization Of Infill Well Locations In Wamsutter Field
This research proposes to optimize the site selection for infill wells in the Wamsutter gas field of the Green River Basin of southwestern Wyoming by utilizing streamline simulation and modified flow simulation methods to address the dynamic connectivity in the reservoir. Unlike conventional static models, this approach will track the continuity of the tight sand reservoirs and well drainage volumes over time.
University of Tulsa (TU), Tulsa, OK 74104
Texas A&M University, College Station, TX 77843
Devon Energy, Oklahoma City, OK 73102
Due to the spatial discontinuity and heterogeneous nature of tight gas reservoirs, selecting the optimal location for infill wells is difficult. Determining the production attributable to a new well is also very challenging as it is hard to tease apart acceleration of production from partially depleted sands already accessed by existing wells and the incremental addition coming from new drainage volumes. Current reservoir models tend to generate artificially low predicted incremental benefits with the addition of infill wells. This occurs due to the lack of preservation of barriers in the reservoir when upscaling the fine-scale geologic models. Upscaling by current methods shows sand connectivity in the reservoir that is not present in the fine-scale model, as it merges pay and non-pay juxtapositions.
This research seeks to account for dynamic connectivity in the reservoir by using a new type of model. By incorporating a time component, the acceleration and incremental components of production from an infill well will be able to be quantified. The innovative model will thus allow for a more accurate prediction of the incremental reserves that will result from the drilling of infill wells. By determining the optimal well spacing and deciding whether drilling an infill well is required to more completely drain the reservoir, the maximum economic benefit will be realized.
The researchers at TU will work with Devon Energy, a provider of financial and technical support, to develop geological and geostatistical models and perform history matching to predict potential performance of infill wells. Recommendations will then be made to Devon Energy on drilling at least one infill well at potential 40-acre locations. Post drilling, the well’s performance will be monitored and then compared with the actual and predicted performance. The model will then be modified if needed.
Deliverables will include monthly status reports, a technical report that details the results of experiments conducted during specific tasks, and a final report. The project performers will make a minimum of two presentations at local professional organization meetings and will submit at least one paper for presentation at an SPE Annual meeting. They will also build and maintain a free website containing information about the project. The final research products will provide a methodology for optimizing infill well locations in tight gas reservoirs and software to be used in the evaluation of other gas fields utilizing a comparable method.
Currently developed with 80-acre spacing, successful identification of high-graded locations of 40-acre spacing wells could increase the potential reserves of the Wamsutter field by as much as 40%. This project will allow for the prediction of a given infill well’s performance and will also provide the opportunity to high-grade locations with the greatest potential benefit. Cost savings will be generated in recognizing locations where no infill wells are needed to deplete the reservoir. The research will be applicable to other tight gas sandstone reservoirs in the Rocky Mountain region and will aid in determining optimal well spacing to maximize the financial benefit in those reservoirs as well.
Work on this project began in early September 2008, and as of yet there have not been any major accomplishments to report with this initial summary.
The first two tasks, the project management plan and the technology status assessment, are under way. The project management plan includes schedules, planned expenditures, major milestones, and decision points for each task. The plan also contains a work breakdown structure and supporting narrative. A summary report on the state-of-the-art of the proposed technology will be the primary element of the technology status assessment. Negative and positive aspects of existing technology alternatives will be described. The nine remaining tasks are described below.
Conduct geostatistical modeling. Working with Devon Energy, TU will identify representative areas within the Wamsutter field. Macro and meso-scopic models of the reservoir architecture will be developed that will illustrate the fine-scale heterogeneities in those areas. Commercial software (PETREL) and state-of-the-art geostatistical procedures will be used to construct the models.
Determine dynamic continuity. Using a novel streamline-based dynamic measure, TU will identify drainage volumes and infill targets in these tight gas reservoirs. The change in drainage volume with time will be quantified. To determine drainage volume, TU will trace streamlines starting from the producing well and then calculate the travel time to the well along the streamlines. The velocities will be obtained using a commercial finite-difference simulator that will take into account the structural, geological, and field complexities.
A time of flight threshold will be used to compute connected drainage volumes so that the connected sands can be incorporated into the upscaled models for simulation and prediction of performance. The time of flight is the distance along the streamline divided by the particle velocity. As new wells are drilled, newly connected volumes will be quantified. Non-connected sands will be eliminated from the fine-scale model model. Virgin sands and previously depleted sands will be modeled, allowing for assessment of infill well performance.
Perform history matching. Simulated well performance will be matched with actual well performance within several representative areas in the Wamsutter field. The rate will be matched by matching near well bore fracture conductivities. Individual layer fracture conductivities will also be matched if production logging tool data are available. The additional connected volume will be incorporated as new wells are drilled. Including these new well volumes is a significant improvement over existing methodologies in history matching.
Predict future well performance. Upon adding the newly connected volumes developed on 40-acre spacing, well performance can be determined. This simulation will separate contributions to performance from acceleration of the depleted sands and the incremental component derived from the newly connected sands. Locations will be high-graded for drilling of infill wells based upon the performance evaluation. TU will recommend that particular wells should be drilled to maximize financial return. Potential uncertainties in fracture conductivities in various reservoir formations will be taken into consideration in predicting performance.
Implement field operations. Based upon TU’s recommendations, at least one 40-acre spacing well will be drilled. Actual well performance will be compared with simulated performance. If the actual performance is not within the bounds of uncertainties, the connected and depleted zones in the model will be modified to match the results. After re-calibration, TU will devise a method for predicting the performance of new wells by determining the connected and depleted volumes alone, with the goal of predicting performance by establishing a correlation between connected volumes and well performance. This would eliminate the need for time-consuming history matching.
Technology transfer. Activities will include the website, reports, presentations, and papers detailed above.
Project Start: September 2, 2008
Project End: September 2, 2010
DOE Contribution: $ 443,563
Performer Contribution: $ 43,568 (University of Tulsa) $2,443,564 (Devon Energy)
RPSEA – Kent Perry (firstname.lastname@example.org or 847-768-0961)
NETL – Virginia Weyland (Virginia.Weyland@netl.doe.gov or 281-494-2517)
University of Tulsa – Mohan Kelkar, Ph.D. (email@example.com or 918-631-3036)
Final Project Report [PDF-9.08] August, 2011