Optimizing economics for unconventional resource development is a delicate balance among four main factors: reservoir deliverability, commodity price, completion design, and well spacing. For a certain reservoir, commodity price, and completion design, there is a well spacing that will optimize field development net present value (NPV). However, if we consider a different part of the reservoir (area or landing zone), commodity price, or completion design, that optimal well spacing changes. Given that this problem is fraught with uncertainty (in price, reservoir deliverability, and the impact on production of changing completion design or well spacing), we need simple, flexible tools to make better decisions about unconventional pad design. From a technical perspective, teams of subsurface professionals strive to understand the relationship between well productivity and well spacing for a given completion design (or vice versa). If the well spacing is too tight relative to the size of fracture stimulation, the recovery factor will be high, but the development plan will be over-capitalized. If the well spacing is too wide relative to the fracture stimulation, the per-well recovery will be high, but too much resource will be left in the ground and the NPV of the development plan will be low. To search for the optimal pad design, operators often invest in integrated technical workflows with multi-well fracture modeling and reservoir simulation; although useful, these workflows are not practical to apply for every asset in a portfolio because they simply take too long. As an alternative approach, this paper builds on existing tools in the literature to quantify the impact of changing well spacing on well productivity for a given completion design, using a new, simple, intuitive empirical equation. Using real data from the Permian basin, this paper applies the empirical equation to model the relationship between well performance and well spacing, and quantify uncertainty in that relationship. By linking this equation with a simple economic model, the paper shows how to make appropriate well spacing decisions under uncertainty, and how those decisions would change due to changes in reservoir deliverability or commodity price. Compared to similar methods in the literature, this approach better captures the physics associated with overlap in drainage areas for adjacent unconventional wells, while maintaining simplicity and ease of implementation. The paper also discusses how to integrate various diagnostics that give information about fracture geometry, to help guide the bounds of uncertainty in the well performance relationship. Even with limited data, this approach can be applied to yield useful information for decision makers about how to adjust unconventional pad design to improve development plan economics.

Characterizing fracture geometry in unconventional reservoirs is essential to optimizing field development. Surveillance data is critical to understand how fractures propagate both vertically and laterally in any given formation. This paper is focused on low-cost, practical solutions to this problem, primarily Sealed Wellbore Pressure Monitoring (SWPM). SWPM is a novel technology recently developed by Devon Energy, which employs a sealed monitoring well to detect the arrival of hydraulic fractures from an adjacent treatment well via a pressure pulse. SWPM has recently been employed in unconventional plays in the U.S. This paper reports the results from its first application in Canada, in the Montney formation in British Columbia. SWPM data was collected from monitoring wells across four pads in the Montney, located in north-east B.C. The Montney consists of multiple stacked development targets, which emphasizes the importance of fracture characterization for optimal well placement and fracture design. Data collected from SWPM was compared with other diagnostics such as production interference testing, and fracture modeling. By integrating the information from these diagnostics, it is possible to better calibrate hydraulic fracture models and make better field development decisions earlier, with more confidence. This paper summarizes the key learnings, challenges, and limitations from the SWPM pilot. In terms of hydraulic fracture geometry, lateral fracture propagation was consistently very fast (long fracture lengths) in the Upper target; whereas in the Middle target, lateral fracture growth was shorter and fracture height growth was greater. This behavior was generally consistent with expectations based on the minimum horizontal stress profile and fracture modeling in the area. The SWPM data correlated reasonably well with production interference tests. A new metric (SWPM Intensity) was found to have the best relationship with the interference test data. This relationship is crucial as it links hydraulic fracture geometry to propped, flowing geometry. In conjunction with other diagnostics, early learnings from SWPM data have already provided significant value in informing field development decisions in the Montney. The novel SWPM Intensity metric provides an early indication of expected production interference between wells, and therefore an indication of how to balance completion intensity with well spacing. Moreover, by better understanding hydraulic fracture geometry and its relationship to propped geometry, completion designs and well spacing can be better customized by layer.