Shale Reservoir Drainage Visualized for a Wolfcamp Well (Midland Basin, West Texas, USA)

Weijermars, Ruud; Harmelen, Arnaud van

doi:10.3390/en11071665

Cited by 14 publications

(11 citation statements)

References 98 publications

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“…The newly completed wells have much higher initial oil rates than the older ones, because they have: (1) longer lateral lengths, (2) bigger hydraulic fractures and (3) more fracture stages [22,[31][32][33][34]. However, the newly completed wells decline faster and have essentially the same ultimate recovery as the older wells.…”

Section: Discussionmentioning

confidence: 99%

“…In the Bakken play, for instance, the newly completed wells have longer lateral lengths, bigger hydraulic fractures and more fracture stages [22,[31][32][33][34]. Thus, we classify the wells in each of the four regions by three completion date intervals: [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012], [2013][2014][2015][2016] and [2017][2018][2019].…”

Section: (C)mentioning

confidence: 99%

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Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale

2019

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We aim to replace the current industry-standard empirical forecasts of oil production from hydrofractured horizontal wells in shales with a statistically and physically robust, accurate and precise method of matching historic well performance and predicting well production for up to two more decades. Our Bakken oil forecasting method extends the previous work on predicting fieldwide gas production in the Barnett shale and merges it with our new scaling of oil production in the Bakken. We first divide the existing 14,678 horizontal oil wells in the Bakken into 12 static samples in which reservoir quality and completion technologies are similar. For each sample, we use a purely data-driven non-parametric approach to arrive at an appropriate generalized extreme value (GEV) distribution of oil production from that sample's dynamic well cohorts with at least 1, 2, 3, . . . years on production. From these well cohorts, we stitch together the P 50 , P 10 , and P 90 statistical well prototypes for each sample. These statistical well prototypes are conditioned by well attrition, hydrofracture deterioration, pressure interference, well interference, progress in technology, and so forth. So far, there has been no physical scaling. Now we fit the parameters of our physical scaling model to the statistical well prototypes, and obtain a smooth extrapolation of oil production that is mechanistic, and not just a decline curve. At late times, we add radial inflow from the outside. By calculating the number of potential wells per square mile of each Bakken region (core and noncore), and scheduling future drilling programs, we stack up the extended well prototypes to obtain the plausible forecasts of oil production in the Bakken. We predict that Bakken will ultimately produce 5 billion barrels of oil from the existing wells, with the possible addition of 2 and 6 billion barrels from core and noncore areas, respectively.

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Section: Discussionmentioning

confidence: 99%

Section: (C)mentioning

confidence: 99%

Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale

2019

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“…Drawbacks of dual and multi porosity-based fracture models are that discrete fractures are not included and actual fracture density is not accounted for. Dual-porosity models also do not account for the flow paths followed when the fluid exchange occurs between the matrix and fractures, which can thus lead to inaccurate modeling of complex flow behaviors and can result in the wrong calculation of pressure gradients [33].…”

Section: Natural Fracture Modelingmentioning

confidence: 99%

“…This stochastic realization method can be used to create multiple realizations of the natural fracture patterns with fracture lengths following a power-law distribution [38]. The DFN method is also computationally intensive (and therefore expensive) as it requires very fine grids, which is particularly the case for multi-stage wells in unconventional reservoirs with numerous perforation zones per well [33].…”

Section: Natural Fracture Modelingmentioning

confidence: 99%

“…This approach was expanded upon to include the Eulerian particle tracking of time-dependent flows with applications to natural lava flows and other gravity flows [50,51]. The basic methodology to describe gravity flows was then applied to flow in subsurface reservoirs, properly accounting for permeability, porosity and fluid volume factors, while benchmarking tests of the CAM using numerical streamline simulations proved highly successful [33,52]. We propose the use of CAM because of it being a gridless meshless method that allows for infinite resolution at the fracture scale and also has faster computational times as compared to gridded numerical simulators.…”

Section: Cam Solution For Hydraulic Fractures and Natural Fracturesmentioning

confidence: 99%

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Impact on Drained Rock Volume (DRV) of Storativity and Enhanced Permeability in Naturally Fractured Reservoirs: Upscaled Field Case from Hydraulic Fracturing Test Site (HFTS), Wolfcamp Formation, Midland Basin, West Texas

Nandlal

Weijermars

2019

Energies

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Hydraulic fracturing for economic production from unconventional reservoirs is subject to many subsurface uncertainties. One such uncertainty is the impact of natural fractures in the vicinity of hydraulic fractures in the reservoir on flow and thus the actual drained rock volume (DRV). We delineate three fundamental processes by which natural fractures can impact flow. Two of these mechanisms are due to the possibility of natural fracture networks to possess (i) enhanced permeability and (ii) enhanced storativity. A systematic approach was used to model the effects of these two mechanisms on flow patterns and drained regions in the reservoir. A third mechanism by which natural fractures may impact reservoir flow is by the reactivation of natural fractures that become extensions of the hydraulic fracture network. The DRV for all three mechanisms can be modeled in flow simulations based on Complex Analysis Methods (CAM), which offer infinite resolution down to a micro-fracture scale, and is thus complementary to numerical simulation methods. In addition to synthetic models, reservoir and natural fracture data from the Hydraulic Fracturing Test Site (Wolfcamp Formation, Midland Basin) were used to determine the real-world impact of natural fractures on drainage patterns in the reservoir. The spatial location and variability in the DRV was more influenced by the natural fracture enhanced permeability than enhanced storativity (related to enhanced porosity). A Carman–Kozeny correlation was used to relate porosity and permeability in the natural fractures. Our study introduces a groundbreaking upscaling procedure for flows with a high number of natural fractures, by combining object-based and flow-based upscaling methods. A key insight is that channeling of flow through natural fractures left undrained areas in the matrix between the fractures. The flow models presented in this study can be implemented to make quick and informed decisions regarding where any undrained volume occurs, which can then be targeted for refracturing. With the method outlined in our study, one can determine the impact and influence of natural fracture sets on the actual drained volume and where the drainage is focused. The DRV analysis of naturally fractured reservoirs will help to better determine the optimum hydraulic fracture design and well spacing to achieve the most efficient recovery rates.

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Visualization of drained rock volume (DRV) in hydraulically fractured reservoirs with and without natural fractures using complex analysis methods (CAMs)

Khanal

Weijermars

2019

Pet. Sci.

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The drainage areas (and volumes) near hydraulically fractured wells, computed and visualized in our study at high resolution, may be critically affected by the presence of natural fractures. Using a recently developed algorithm based on complex analysis methods (CAMs), the drained rock volume (DRV) is visualized for a range of synthetic constellations of natural fractures near hydraulic fractures. First, flow interference effects near a single hydraulic fracture are systematically investigated for a variety of natural fracture sets. The permeability contrast between the matrix and the natural fractures is increased stepwise in order to better understand the effect on the DRV. Next, a larger-scale model investigates flow interference for a full hydraulically fractured well with a variety of natural fracture sets. The time of flight contours (TOFCs) outlining the DRV are for all cases with natural fractures compared to a base case without any natural fractures. Discrete natural fractures, with different orientations, hydraulic conductivity, and fracture density, may shift the TOFC patterns in the reservoir region drained by the hydraulically fractured well, essentially shifting the location of the well's drainage area. The CAM-based models provide a computationally efficient method to quantify and visualize the drainage in both naturally and hydraulically fractured reservoirs. Keywords Natural fracture • Drained rock volume • Drainage area distortion • Hydraulic fractures Abbreviations CAM Complex analysis methods DRV Drained rock volume TOFC Time of flight contours SRV Stimulated reservoir volume DFN Discrete fracture network List of symbols Complex potential m Strength of point/interval sources υ Strength of the natural fractures V Velocity potential γ Tilt angle of the natural fractures x c Center of the interval source L Length of the interval source Angle of the interval source L k Total length of interval source k m k Strength of interval source k h Reservoir thickness B Formation volume factor v x Velocity in the x-direction v y Velocity in the y-direction Δt Time-step

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Shale Reservoir Drainage Visualized for a Wolfcamp Well (Midland Basin, West Texas, USA)

Cited by 14 publications

References 98 publications

Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale

Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale

Impact on Drained Rock Volume (DRV) of Storativity and Enhanced Permeability in Naturally Fractured Reservoirs: Upscaled Field Case from Hydraulic Fracturing Test Site (HFTS), Wolfcamp Formation, Midland Basin, West Texas

Visualization of drained rock volume (DRV) in hydraulically fractured reservoirs with and without natural fractures using complex analysis methods (CAMs)

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