In recent years, the number of horizontal wells drilled in the Permian basin of West Texas has increased. The Wolfcamp Shale is a prime target for horizontal well drilling because of its high liquids potential, which makes it an economically viable play. Ensuring maximum reservoir contact and successful hydraulic fracturing can be challenging in the Wolfcamp Shale, which is known for its highly heterogenous nature, high clay content, and high in situ stress.In the past, Clayton Williams Energy has had limited success stimulating its horizontal wells in the Wolfcamp Shale. These issues can be partially attributed to the highly stressed, laminated and heterogeneous nature of the formation. The conventional geometrically spaced perforation program that is typically selected when log data is not available or is not considered in the engineering design process can result in high pressure differentials between perforation clusters within a stage. The consequence of this includes reduced reservoir contact, incomplete proppant placement, screenouts, and skipped stages in parts of the lateral that are landed in higher stressed rock.In this study, openhole logging services acquired data through a specialized drill bit. These measurements were then integrated in an engineered staging and perforating workflow. The raw log data was processed to provide both petrophysical and geomechanical rock properties, which were used as inputs to quantify reservoir quality (RQ) and completion quality (CQ) for the engineered completion workflow. The workflow intelligently locates fracture stages and perforations by placing perforation clusters within a given stage in similar stressed rock as opposed to conventional geometric staging, which uniformly spaces out perforation clusters without accounting for the variability in rock properties along the lateral. The workflow honors the desired cluster spacing as much as the stress heterogeneity will allow. This optimization workflow was applied to a number of horizontal wells in the Wolfcamp formation of the Delaware basin in West Texas.The successful application of log measurements in the lateral for an engineered completion workflow resulted in the first stimulation treatment being placed 100% as designed with no issues. Three wells with log measurements where the engineered completion workflow was implemented showed, on average, a 67% increase in 90 days cumulative barrels of oil equivalent per lateral length compared to three geometric wells in the same area. A 28% increase in designed sand volume was pumped, and the operator also realized a 33% increase in successful stages, where more than 75% of the designed sand volume was pumped. The engineered completion workflow presented below describes a process that is meant to increase the effectiveness of stimulation treatments in horizontal well completions by increasing the percentage of perforation clusters that are stimulated and contributing to production.A 3D multiwell reservoir model was also designed using well log information from vertic...

Horizontal well performance in shale gas plays is highly dependent on placing the well in the preferred target zone of the reservoir interval. Some operators who drill in shale plays do not have seismic data and depth structural maps. They plan their horizontal wells with only offset well data. Sometimes, their wells land outside of the preferred target because they blindly place horizontal wells by using only non-directional gamma ray (GR) log data. For optimal well planning and placement for optimized production, it is important to minimize uncertainty about reservoir structure and placement. Usually, operators create a depth map from identified markers such as well tops correlated across available wells in the field. The generated map is limited and often leads to landing laterals outside the target zone, especially when well control is not ideal. The aim of this paper is to illustrate a method of building structural maps and 3D geologic models for drilling in shale gas reservoirs. This methodology lends itself particularly well (but not exclusively) to the pad drilling approach common in shale gas development. The use of logging-while-drilling (LWD) technology can be strategically planned from pad to pad to help mitigate structural uncertainty. Data from 42 horizontal and 6 vertical wells in the project area allowed real-time density image and azimuthal logs to be coupled with vertical offset well information to model the structure along the drilled horizontal well trajectory. The model integrated all the well tops and real-time bedding dip information to produce modeled surfaces. The structural model generated during this study can be used for new well landing-point planning with limited true vertical depth uncertainty and for other fieldwide reservoir characterization. If structure information becomes available from seismic data, this technique also can be used to update the structural model derived from seismic interpretation, thereby delivering enhanced structural control of the field.

For a well in the Permian Basin, openhole (OH) triple combo logs from five nearby offset wells and gamma ray from a horizontal well were used to deduce a workflow to define the 3D structural geometry of the drilled horizontal section. After establishing the structural architecture of the drilled lateral section to determine which part of the lateral is in or out of zone, lithology and petrophysical properties from the offset wells were propagated using geostatistical algorithms to match the horizontal well path. A relatively distant offset well with an advanced log suite was also utilized to generate synthetic mechanical rock properties along the lateral. These data were used for optimized completion design by placing stimulation stages in similar rock and intelligently placing perforation clusters. Placement was guided by rock type and geomechanical properties as opposed to geometrical spacing along the lateral. The assumption that rock properties are homogenous and structural dip is fairly constant in horizontal drilling has been proven to be untrue in recent studies, and production logs have shown that not all stages/perforation clusters contribute to production. The consequence of not using image log measurements in geosteering the lateral to ensure that the lateral is in the target reservoir can lead to ineffective stimulation treatment and possibly skipping stages in parts of the lateral that is landed in a higher stress rock. The successful application of the workflow enabled us to determine the structural geometry along the drilled horizontal well and also build a 3D structural and property model, which was successfully used for the optimized stimulation staging and completion design. This produced a more successful stimulation treatment with approximately 67% more sand placed per stage compared to an offset well drilled in the same target zone.