Plunger lifted, and free-flowing gas wells experience a wide range of issues and operational inefficiencies such as liquid-loading, downhole and surface restrictions, stuck or leaking motor control valves, and metering issues. These issues can lead to extended downtime, equipment failures, and other production inefficiencies. Using data science and machine-learning algorithms, a self-adjusting anomaly detection model considers all sensor data, including the associated statistical behavior and correlations, to parse any underlying issues and anomalies and classifies the potential cause(s). This paper presents the result of a Proof of Concept (PoC) study conducted for a South Texas operator encompassing 50 wells over a three-month period. The results indicate an improvement compared to the operators’ visual inspection and surveillance anomaly detection system. The model allows operators to focus their time on solving problems instead of discovering them. This novel approach to anomaly detection improves workflow efficiencies, decreases lease operating expenses (LOE), and increases production by reducing downtime.

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Hydraulic fracturing and horizontal well drilling technologies have enabled the oil and gas industry to safely unlock large reserves of oil and gas in unconventional resources, especially in shale gas and oil, and tight gas and tight oil reservoirs. However, there is an ongoing debate on whether "the best practice" is to drill a horizontal well in the direction of minimum horizontal stress, which would create transversely fractured well or to drill the well in the direction of maximum horizontal stress, which would create longitudinally fractured well. Additionally, little work has been done to understand the complex relationship that exist between principal stresses, well azimuth and/or lateral direction. This paper presents the results of a comprehensive multiphase flow study that investigated the relationship between the principal stresses and lateral direction in hydraulically fractured horizontal wells, and its impact on well performance. Secondly, the study also incorporated previous studies, where applicable, of a single phase flow study that was conducted by the co-authors of this paper. Both studies focused on transversely fractured wells versus longitudinally fractured wells, and how well azimuth affects productivity, reserves and economics of horizontal wells. The previous study primarily focused on wells that produced single phase fluids, and used single phase reservoir numerical models to study well performance. The study investigated the importance of lateral direction as a function of reservoir permeability, lateral length, fracture-half length, number of fracture stages, fracture conductivity, and well completion type (open-hole vs cased-hole). The Single phase study also included a number of actual field cases where the results were compared to actual wells in both oil and gas reservoirs that had transversely fractured or longitudinally fractured horizontal wells. This study would extend the findings of the single phase flow study by adding multiphase flow dimensions such as effects of relative permeability, non-Darcy flow, adsorption gas, stress dependent permeability on induced fractures and conductivity changes in the fracture from the tip to the wellbore. The study used black oil reservoir simulator to study two phase flow mechanisms such as gas-water (dry gas reservoir) and under-saturated oil reservoir (oil-water), and compositional reservoir simulator to model three-phase flow (oil-gas-water) to investigate each parameters' impact on well performance. This study is unique as it examines the permeability ranges from wells with 1 Nano-Darcy (0.000001 md) to 10.0 milli-Darcy in a multiphase flow reservoir simulation. Additionally, this paper presents the first multiphase flow study that thoroughly compared the performance of transversely fractured versus longitudinally fractured horizontal wells. Key features of the study that would benefit the petroleum industry are; Methodologies for modeling shale gas and shale oil wells with stress dependent permeability, adsorption gas and non-Darcy flow effect using black oil models and compositional reservoir simulators.Reservoir permeability based cut-off criterion that can be used as guide when selecting whether to drill transversely fractured vs longitudinally fractured horizontal wells.Integrating the reservoir objectives and geo-mechanical limitations into horizontal well completions and stimulation strategies.Incorporate the effect of reservoir fluid type and fluid properties such as oil composition and density (API) into the decision analysis when comparing transverse horizontal wells to longitudinal horizontal wells.Stimulation optimization strategies focused on well recovery, productivity and EUR as function of hydraulic fracture spacing (or number of fracture stages) and reservoir permeability

The Montney Formation stretches from southwestern Alberta to northeast British Columbia in Canada, and is one of the largest and most prolific shale plays in North America. The Montney Formation is also unique because it has conventional, over-pressured gas and an over-pressured liquids rich fairway. However, since the first multiple fractured horizontal well was drilled in 2005, there has been proposals for optimizing completions using different fracturing fluid systems and completion techniques. The low oil and gas price environment and the ensuing cost control mechanisms coupled with better understanding of what works in the Montney Formation, made the utility of some of the previously proposed optimization designs like "fracture effectiveness" which used energized fracturing fluids less desirable completions method. However, completion optimization methods like "operational effectiveness" which used high-rate slick water with increasing proppant mass per stage become the dominant stimulation method in the Montney Formation. But what has been missing was how to integrate fracture design and optimizations using all available information such as step-rate test, mini-frac, DFIT (diagnostic fracture injection test) analysis, well logs, geo-mechanical data, fracability index, core data, micro-seismic mapping data, and post-fracture analysis to improve fracture design and optimize the well completions. The objective of this paper is to present a new methodology for building calibrated fracture models from low quality micro-seismic data that has either location uncertainty or signal-to-noise ratio issues, and use it to optimize well completions. The process involves two-steps; first, the hydraulic fracture design was modeled and then calibrated using only micro-seismic mapping data from fracture stages that were closest to the micro-seismic geophones (avoiding location uncertainty or signal-to-noise ratio issues). This allowed us to construct a robust and reliable fracture geometry model. For each of the wells in the study, all fracture stages were then history matched and remodeled using the calibrated fracture model. Secondly, each well was optimized by incorporating fracture cluster sensitivity (2, 3, 4, and 5 clusters per stage), proppant mass sensitivity (50 kg, 75 kg, 100 kg, and 150 kg per stage) and fracture spacing sensitivity (20 m, 25 m, 33 m, 49 m and 98 m per stage). The result from this study shows that a highly optimized fracture model can be constructed from low quality micro-seismic mapping data that had location uncertainty due to the use of one monitoring well or signal-to-noise ratio issues. Secondly, the result also shows that increasing the number of clusters per stage and proppant mass per stage improves well production and recovery. However, the question is are these improvements short time gains, and what is the balance between well productivity and economics? Thirdly, in this study, we propose using measureable and known metrics to optimize wells such as average "hydraulic" fracture half-length, propped fracture half-length and conductivity for multi-clustered fracture stages. Ideally, well performance should be obtained from lookbacks instead of pounds per lateral length of the horizontal well (i.e. 2,400 lb. /ft.) or fixed volume/proppant for each stage or fixed clusters per stage without any empirical data to support it. While there are no two shale formations that are alike, most of the findings from this study are transferable and applicable to other unconventional resources. For instance, the paper presents; A new method for building calibrated fracture models from low quality micro-seismic mapping data that has location uncertainty or signal-to- noise ratio issues.A new method for optimizing fracture designs using cluster sensitivity analysis with varying proppant mass per fracture stage that can be used for scenarios analysis.A methodology for optimizing fracture design models by adjusting fracture treatment volumes and proppant mass per stage based on well stage location and available net treatment pressure.

The Montney Formation which stretches from Alberta to British Columbia is one of the largest unconventional gas resources in North America. Production from the Montney Formation comes primarily from the Upper Montney and Lower Montney Formations which vary both from reservoir quality and geomechanical perspectives. Historically, completion and stimulation optimization fell into two distinct categories (1) field observation supported by reservoir and fracture simulation or (2) statistical analysis. Few, if any, statistical studies on optimizing unconventional completions and fracture stimulation combined information from the statistical analysis with that of the simulation. This paper does just that for the Montney Formation by comparing and contrasting the Upper and the Lower Montney completions and fracture stimulation statistical results with a reservoir and fracture simulation study to better understand key drivers for successful stimulation of multiple fractured horizontal wells. Previous work (Mohammed et al. 2016) documented the statistical analysis of 296 cased-hole horizontal gas wells' completions in the Upper and the Lower Montney Formation. The study showed the effect of cased-hole completion and stimulation parameters on gas production performance in both the Upper and the Lower Montney Formations. In this paper, previous statistical results were extended by adding hydraulic fracture modeling using 3D finite element simulator. The results from the statistical analysis and hydraulic fracture modeling were compared on a set of parameters such as the effect of the number of clusters per stage (1-to-5), changes in proppant mass (50% decrease or increase) and treatment volumes. The results also show the effect of cluster spacing and proppant type on fracture dimensions and production performance within the Upper and the Lower Montney Formation. This study investigated fracture performance to find the best fracturing practices for the Upper and the Lower Montney. This wok benefits the industry by: Providing a solid simulation study of horizontal gas wells with cased-hole completion, which compared fracture performance for the Upper and the Lower Montney Formation.Providing comparison of multiple fractured horizontal wells' performance in the Upper and the Lower Montney Formation based on the number of clusters per stage and treatment volume.Identifying factors that affect cased-hole completions and stimulation performance in the Upper and the Lower Montney Formation.By conducting fracture cluster optimization study to determine the effect of the number of clusters, cluster spacing and proppant type on fracture dimensions and well performance.