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Abstract To economically and efficiently develop unconventional resource plays, the industry has been spending tremendous resources to optimize completion and well spacing by piloting – a trial-and-error approach. However, the approach tends to take long time and cost significant amount of money. As the complex fracturing modeling technology advances, we question: "Can we use the latest complex fracturing modeling and reservoir simulation technologies to optimize completion and well spacing?", so that the industry can significantly save piloting time and money, and quickly find the optimal well spacing and corresponding optimal completion. A recent case study in Permian Basin has answered the question well. For a Wolfcamp well completed with crosslinked gel and wide cluster spacing in 2012, we first built a 3-D geological and geomechanical model, and a full wellbore fracturing propagation model, and then calibrated it with multi-stage fracturing pumping history; the resulting complicated fracture network model was then converted into an unstructured grid-based reservoir simulation model, which was then calibrated with the well production history. During the process, discrete natural fracture network (DFN) and stress anisotropy were systematically evaluated to study their impact on fracture growth. Microseismic and tracer log data were used to validate the hydraulic fracturing modeling results. To test if the calibrated geomechanical and reservoir models can be used to optimize well completion design, we then ran the fracturing model with the latest completion design (tighter cluster spacing, slick-water, and more fluid and proppant) and forecasted the well performance. We found out that the resulting well performance is very similar to the performance of those wells with similar completion designs in the same area. After establishing the confidence on the capacity of those models, we then further studied the impact of different completion designs on fracture dimensions and well performance. We examined the distributions of fracture length along the wellbore resulted from different cluster spacings, fracturing fluid types and volume, and proppant amount. We found out (1) the hydraulic fracture length and network complexity mainly depend on DFN and stress anisotropy, and fracturing fluid viscosity; and (2) the fracture length of those fractures initiated from different perforation clusters along wellbore is in a log-normal distribution depending on completion designs, which provides crucial insights to well interference and furthermore on well spacing. Therefore, we can reasonably model complicated fracture propagation and corresponding well performance with the latest modeling technologies, and then optimize well spacing, which should help operators save significant time and money on well completion and spacing piloting projects, and thus speed up field development decision. The paper demonstrates our novel workflow as an effective way to optimize completion design and well spacing by integrating advanced multi-stage fracture modeling with reservoir simulation in unconventional resource plays.
- North America > United States > Wyoming > Laramie Basin > Niobrara Formation (0.99)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- (31 more...)
- Information Technology > Modeling & Simulation (1.00)
- Information Technology > Communications > Networks (0.48)
- Information Technology > Artificial Intelligence > Representation & Reasoning (0.46)
Over the past decade, microseismic monitoring, a technology developed for evaluating completions of wells drilled to produce hydrocarbons from unconventional reservoirs, has grown increasingly popular among oil and gas companies. This book discusses how to process microseismic data, what can and cannot be inferred from such data, and to what level of certainty this might be possible. The narrative of the book follows the passage of seismic waves: from a source triggered by hydraulic fracture stimulation, through hydrocarbon-bearing formations, towards motion sensors. The waves' characteristics encode the location of their source and its focal mechanism. The analysis of various approaches to harvesting the source-related information from microseismic records has singled out the accuracy of the velocity model, fully accounting for the strong elastic anisotropy of hydraulically fractured shales, as the most critical ingredient for obtaining precise source locations and interpretable moment tensors. The ray theory complemented by its modern extensions, paraxial and Fréchet ray tracing, provides the only practical means available today for building such models. The book is written for geophysicists interested in learning and applying advanced microseismic data-processing techniques.
- North America > United States > Texas (1.00)
- North America > United States > North Dakota (1.00)
- North America > United States > New Mexico (1.00)
- (11 more...)
- Overview (1.00)
- Summary/Review (0.87)
- Research Report > New Finding (0.45)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (1.00)
- Geology > Structural Geology > Fault (1.00)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play (1.00)
- (5 more...)
- Government > Regional Government > North America Government > United States Government (1.00)
- Energy > Renewable > Geothermal > Geothermal Resource (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- North America > United States > Wyoming > Powder River Basin > Sussex Formation (0.99)
- North America > United States > Wyoming > Laramie Basin > Niobrara Formation (0.99)
- North America > United States > Utah > Paradox Basin > Greater Aneth Field > Aneth Field > Paradox Formation > Desert Creek Zone (0.99)
- (77 more...)
- Well Completion > Hydraulic Fracturing (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (0.92)
- Information Technology > Data Science > Data Quality (0.92)
- Information Technology > Artificial Intelligence > Machine Learning (0.67)
- Information Technology > Communications > Networks > Sensor Networks (0.33)