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ABSTRACT The industry is facing significant challenges due to the recent downturn in oil prices, particularly for the development of tight reservoirs. It is more critical than ever to 1) identify the sweet spots with less uncertainty and 2) optimize the completion-design parameters. The overall objective of this study is to quantify and compare the effects of reservoir quality and completion intensity on well productivity. We developed a supervised fuzzy clustering (SFC) algorithm to rank reservoir quality and completion intensity, and analyze their relative impacts on wells' productivity. We collected reservoir properties and completion-design parameters of 1,784 horizontal oil and gas wells completed in the Western Canadian Sedimentary Basin. Then, we used SFC to classify 1) reservoir quality represented by porosity, hydrocarbon saturation, net pay thickness and initial reservoir pressure; and 2) completion-design intensity represented by proppant concentration, number of stages and injected water volume per stage. Finally, we investigated the relative impacts of reservoir quality and completion intensity on wells' productivity in terms of first year cumulative barrel of oil equivalent (BOE). The results show that in low-quality reservoirs, wells' productivity follows reservoir quality. However, in high-quality reservoirs, the role of completion-design becomes significant, and the productivity can be deterred by inefficient completion design. The results suggest that in low-quality reservoirs, the productivity can be enhanced with less intense completion design, while in high-quality reservoirs, a more intense completion significantly enhances the productivity. Keywords Reservoir quality; completion intensity; supervised fuzzy clustering, approximate reasoning,tight reservoirs development
Rodríguez-Pradilla, Germán (School of Earth Sciences, University of Bristol, UK.) | Eaton, David (Department of Geoscience, University of Calgary, Canada.) | Popp, Melanie (geoLOGIC Systems Ltd., Calgary, Canada.)
Abstract The goal of this work is to calibrate a regional predictive model for maximum magnitude of seismic activity associated with hydraulic-fracturing in low-permeability formations in the Western Canada Sedimentary Basin (WCSB). Hydraulic fracturing data (i.e. total injected volume, injection rate, and pressure) were compiled from more than 40,000 hydraulic-fractured wells in the WCSB. These wells were drilled into more than 100 different formations over a 20-year period (January 1st, 2000 and January 1st, 2020). The total injected volume per unit area was calculated utilizing an area of 0.2° in longitude by 0.1° in latitude (or approximately 13x11km, somewhat larger than a standard township of 6x6 miles). This volume was then used to correlate with reported seismicity in the same unit areas. Collectively, within the 143 km area considered in this study, a correlation between the total injected volume and the maximum magnitude of seismic events was observed. Results are similar to the maximum-magnitude forecasting model proposed by A. McGarr (JGR, 2014) for seismic events induced by wastewater injection wells in central US. The McGarr method is also based on the total injected fluid per well (or per multiple nearby wells located in the same unit area). However, in some areas in the WCSB, lower injected fluid volumes than the McGarr model predicts were needed to induce seismic events of magnitude 3.0 or higher, although with a similar linear relation. The result of this work is the calculation of a calibration parameter for the McGarr model to better predict the magnitudes of seismic events associated with the injected volumes of hydraulic fracturing. This model can be used to predict induced seismicity in future unconventional hydraulic fracturing treatments and prevent large-magnitude seismic events from occurring. The rich dataset available from the WCSB allowed us to carry out a robust analysis of the influence of critical parameters (such as the total injected fluid) in the maximum magnitude of seismic events associated with the hydraulic-fracturing stimulation of unconventional wells. This analysis could be replicated for any other sedimentary basin with unconventional wells by compiling similar stimulation and earthquake data as in this study.
As fields are discovered, and subsequently developed, operators play with a variety of well spacing, landing depths, and frac designs. This study focuses on the Montney development and examines the effect of adding additional wells to pad locations on midterm production forecasting. The Western Canadian Sedimentary Basin is replete with data due to the regulatory practices in the resource-rich provinces.
Pads with some level of infill drilling since 2018 were identified and grouped by azimuthal direction to assign families. The forecasting tool is a physio-statistical method that works best when peak rate is achieved or with six months of production. Wells with less than six months of production were filtered out. There were 32 pads identified, 13 of which were in the same field (Heritage) and zone (Montney). Each pad was studied while considering fracture treatment design, spacing (inter-wellbore and in stratigraphic column), and timing.
Of these 13 pads, two pads showed an improvement to the primary wells’ forecasts, two showed no change, and the majority (nine) showed a decrease in primary well production. Finally, a study of the effect of shutting wells in on both the individual well and the pad was conducted to evaluate if the production handicap was a result of competitive drainage (primary-infill interactions) or near wellbore phase behaviors (shut-in effects).
This paper attempts to answer the question: what would the primary well have produced had it not been impacted by infill activity? A majority of the work that has been presented on this subject tends to focus on either the short term impact of fracture hits (Daneshy, 2020) (Yang, 2020). In contrast, this study focuses on midterm production forecasts (3–5 years of total well life), which would typically be the desired payout period for a lot of these wells.
The Montney Formation in Western Canada has been actively drilled and completed with horizontal multi-stage fractured wells since 2005. There have been over 8,000 horizontal multi-stage wells drilled in the play as of May 19, 2020, with multiple operators active (Figure 1).
Abstract For the vast majority of civilization, humans died in a world that looked very much like it did when they were born. But recently, the exponential growth of technology has fundamentally shifted the world's systems and the humans that occupy them. The oil and gas industry struggles with the question of how it will adopt and adapt in light of these technological advancements. A major driver in the current market uncertainty is choosing a technology that will provide optimal learning for the least amount of effort, money, and time. In this paper, the benefit of using a technological advantage is explored from the point of view of generating type curves and forecasting well production. Traditional decline curve methods are founded on analytical expressions from the 1940s that are strictly based on empirical observations. Currently, engineers and analysts use a mix of these contemporaneous methods (and derivations thereof) and area expertise in their technical assessments to forecast well production. This type of analysis can introduce a level of bias which makes it very difficult, if not impossible, for two independently generated forecasts to be meaningfully reconciled against one another. Introduction This two-part study explores a data-driven physio-statistical method for deriving production forecasts. The predictive analytical model underpinning this method has been trained on over 200,000 conventional and unconventional wells drilled in various plays with an extensive range of depositional environments, completion types, vintages, fluid properties, and operating conditions. Using solutions to differential equations to ensure that forecasts are generated honouring the fundamentals of fluid flow, provides accurate, unbiased, repeatable, and validated results. This paper is based on work for a study area that encompasses 29 horizontal Montney gas wells in NE British Columbia. In part 1 of this study, production forecasts generated by the physio-statistical model (the Model) are compared to those generated by an experienced human reservoir engineer (HRE). The latter used a sophisticated commercially available decline curve analysis toolkit modified for unconventional reservoirs. Forecasted production volumes were compared against 12-months of actual production data and the suitability and limitations of the Model's forecasts are discussed.