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Abstract In some basins, large scale development of unconventional stacked-target plays requires early election of well targeting and spacing. Changes to the initial well construction framework can take years to implement due to lead times for land, permitting, and corporate planning. Over time, as operators wish to fine tune their development plans, completion design flexibility represents a powerful force for optimization. Hydraulic fracturing treatment plans may be adjusted and customized close to the time of investment. With a practical approach that takes advantage of physics-based modeling and data analysis, we demonstrate how to create a high-confidence, integrated well spacing and completion design strategy for both frontier and mature field development. The Dynamic Stimulated Reservoir Volume (DSRV) workflow forms the backbone of the physics-based approach, constraining simulations against treatment, flow-back, production, and pressure-buildup (PBU) data. Depending on the amount of input data available and mechanisms investigated, one can invoke various levels of rigor in coupling geomechanics and fluid flow – ranging from proxies to full iterative coupling. To answer spacing and completions questions in the Denver Basin, also known as the Denver-Julesburg (DJ) Basin, we extend this modeling workflow to multi-well, multi-target, and multi-variate space. With proper calibration, we are able generate production performance predictions across the field for a range of subsurface, well spacing, and completion scenarios. Results allow us to co-optimize well spacing and completion size for this multi-layer column. Insights about the impacts of geology and reservoir conditions highlight the potential for design customization across the play. Results are further validated against actual data using an elegant multi-well surveillance technique that better illuminates design space. Several elements of subsurface characterization potentially impact the interactions among design variables. In particular, reservoir fluid property variations create important effects during injection and production. Also, both data analysis and modeling support a key relationship involving well spacing and the efficient creation of stimulated reservoir volumes. This relationship provides a lever that can be utilized to improve value based on corporate needs and commodity price. We introduce these observations to be further tested in the field and models.
Abstract Accelerating the learning curve in the development of the Vaca Muerta utilizing lessons learned in North American unconventional resource plays is the focus of this paper. Reducing completion costs while maintaining high productivity has become a key objective in the current low-price environment. Completion diagnostics have been demonstrated to optimize stimulation and completion parameters that have shaped successful field developments. The paper reviews stimulation diagnostic data from wells completed in the Tuscaloosa Marine Shale, Eagle Ford, Wolfcamp and Niobrara shale formations. Case histories are presented in which proppant and fluid tracers were successfully employed in completion optimization processes. In the examples presented, diagnostic results were used to assess the stimulation of high productivity intervals within a target zone, evaluate various completion methods, and optimize stage and cluster spacing. The diagnostic data were compared with post-frac production rates in an effort to correlate completion changes with well performance. Results presented compare first, engineered perforations versus conventional geometrically spaced perforations to drive up effectiveness in cluster stimulation. Second, new chemistries, such as nanosurfactant, versus conventional chemistries to cut either completion cost or prove their profitability. Third, employing an effective choke management strategy to improve well productivity. Last, as in any stacked pay, determining fracture height growth in order to optimize well density, well spacing, field development and ultimately the recovery of the natural resources. Completion effectiveness is shown to be improved by landing laterals in high productivity target intervals, increasing proppant coverage across the lateral by utilizing the most effective completion methods, optimizing cluster spacing and decreasing the number of stages to reduce completion costs while achieving comparable production rates. Cluster treatment efficiency (CTE), in particular, has become a critical metric when optimizing hydraulic fracturing treatment designs based on current and future well densities. It can be used to rationalize well performance as well as to identify possible candidates for a refrac program. Using completion diagnostics, successful completion techniques were identified that led to production enhancements and cost reductions in prolific plays such as the Tuscaloosa Marine Shale, Eagle Ford, Wolfcamp and Niobrara.
ABSTRACT: Heterogeneity of an unconventional reservoir is one of the main factors affecting production. Well performance depends on the size and efficiency of the interconnected fracture “plumbing system”, as influenced by multistage hydraulic fracturing. A complex, interconnected natural fracture network can significantly increase the size of stimulated reservoir volume, provide additional surface area contact and enhance permeability. The purpose of this study was to characterize the natural fracture patterns occurring in the unconventional Niobrara reservoir and to determine the drivers that influenced fracture trends and distributions. Highly fractured areas/fracture swarm corridors were identified and integrated into a reservoir model though DFN (Discrete Fracture Network) application for further prediction of reservoir performance using reservoir simulations. The predictive capability of DFN models can aid in improved reservoir performance and hydrocarbon production through optimized well spacing, re-frac stage locations planning for existing wells as well as completion strategies design for new wells.