Well-Spacing Study to Develop Stacked Tight Oil Pay in Midland Basin

Abstract

Tight formations are being developed by drilling in the Midland Basin. Target intervals include Clearfork, Wolfcamp, Spraberry, Strawn, Cline, Atoka, and Mississipian formations, which are usually found between 6000 feet and 11,500 feet true vertical depth (TVD). Development is typically with vertical wells, which are stimulated with multiple hydraulic fractures targeting the expected pay intervals and are produced commingled. A significant challenge for operators is determining the optimum well locations and spacing for efficient reserve development. Operators use various field data and analytics to determine well spacing, although limited data pose challenges to making the best decisions. Numerical models can yield insights about drainage patterns and potential interference. This paper reports a case study using a geologic model, hydraulic stimulation models, and a reservoir simulation model to evaluate reduced well spacing impacts on recovered oil and economics. A three-dimensional geologic model was constructed for a 14-section area in the Midland Basin. An extensive core-log statistical study yielded calibrated rock types at the wells. Reservoir and geomechanical properties were then spatially distributed using geostatistical techniques subject to data constraints. A reservoir simulation model was then utilized on a sector area of the full model. The sector model was history-matched to early production data and historical type curves. Each well had 10–12 fracture stages, which were explicitly modeled using parameters derived from post-execution analysis of fracture job data. The paper presents history-matched simulation models that were executed to predict production and economics for 40-acre and 20-acre well spacing cases.

Status and Outlook of Oil Field Chemistry-Assisted Analysis during the Energy Transition Period

“…Another issue is that many horizontal wells are drilled in stacked mode and developed as “three-dimensional.” , Infill wells are drilled among many old wells to improve recovery efficiency. , Well-to-well interaction and communication are easy to occur, so the accurate development of unconventional oil and gas reservoirs needs a high-resolution fluid origin tracing technique with very fine stratigraphic intervals between 3 to 6 m. , …”

Stimulated Reservoir Volume Characterization and Optimum Lateral Well Spacing Study of Two-Well Pad: Midland Basin Case Study

“…The key features of CMG IMEX for unconventional reservoirs include local grid refinement (LGR), modeling biwing hydraulic fractures and complex hydraulic fracture network, and comprehensive horizontal well management [14]. A number of existing body of well spacing studies in hydraulically fractured unconventional reservoirs [5,6,15] have utilized CMG IMEX. The current study utilizes LGR and biwing hydraulic fractures to represent the part of the reservoir stimulation.…”

“…There have been studies to investigate the optimum well spacing in the development of tight shale reservoirs in the Permian Basin, utilizing the physic-based reservoir simulation work. Cullick and Carrillo [5] studied well spacing for vertical wells fractured from Spraberry to Atoka to develop stack tight oil pay in the Midland Basin. Pettegrew and Qiu [6] utilized data analytics and reservoir simulations to determine the relationship between EUR and well spacing for the Wolfcamp formation in the Delaware Basin.…”

Optimising well orientation in hydraulic fracturing of naturally fractured shale gas formations

“…Analytical modelling has shown that reservoir permeability and the fracture area are the most important factors to consider when optimising the well spacing (Lalehrokh & Bouma, 2014). Numerical studies have also shown the challenges of determining optimal stage and cluster spacing when J o u r n a l P r e -p r o o f 3 considering complex geological models (Cullick et al, 2014). In a study conducted by Sahai et al, numerical simulations have been used to model the recovery from large areas to determine optimal spacing focussing on the production from stimulated reservoir volumes (SRV) and external reservoir volumes (XRV) (Sahai et al 2012).…”