This is a continuation of the previous list of 29 papers and 1 patent:
30. Zhu, W., Khirevich, S., & Patzek, T. W. (2021). Impact of fracture geometry and topology on the connectivity and flow properties of stochastic fracture networks. Water Resources Research, 57, e2020WR028652. https://doi.org/10.1029/2020WR028652Natural fractures usually comprise complex networks and control many physical properties of rocks, including stiffness, strength, and permeability. Therefore, they significantly impact many engineering fields, such as hydrology, waste disposal, geothermal exploitation, and petroleum reservoir exploitation. In a low permeability formation, fractures play a dominant role because the contribution of the matrix to fluid flow is almost negligible. Connectivity of natural and induced fractures thus determines the overall capability of fluid flow of subsurface rocks. Commonly used approaches to evaluate the connectivity (percolation method, connectivity index/field, and intersection index) are insufficient to capture the impacts of all geometrical properties of arbitrary fracture networks. Therefore, we utilize a topological concept of global efficiency to investigate the key geometrical properties of two-dimensional (2D)/three-dimensional (3D) stochastic fracture networks quantitively. After analyzing thousands of realizations of stochastic fracture networks, our results show that geometrical properties, including fracture lengths, apertures and positions of fracture centers, influence the connectivity of fracture networks. Aperture variations cause a significant change in connectivity of a fracture network, especially for fracture networks dominated by large fractures. Clustered and small fractures usually lower global efficiency in both 2D and 3D fracture networks. Similar conclusions are valid in realistic fracture networks composed of several sets of fractures with constrained preferred orientations.
We present a hybrid, data-driven and physics-based method of forecasting play-wide gas production in the Haynesville Shale, which is currently the second-largest shale gas producer in the US. We first define several statistical well cohorts, one for each reservoir quality and each well completion technology in the Haynesville. For each cohort, we use the Generalized Extreme Value (GEV) statistics to obtain the historical average well prototypes. The cumulative production of each well prototype is matched with a physics-based scaling curve, and its production is then extrapolated for up to two more decades. The resulting well prototypes are exceptionally robust. If we replace individual production rates from all existing wells with their corresponding well prototypes and sum them up, the total rate will match remarkably the past gas field rate, and – in this case – we obtain a base or do nothing forecast. Next, we calculate the number of potential infill wells per square mile and schedule future drilling programs to obtain plausible production forecasts in the Haynesville. Because Haynesville is the most active shale play in North America in terms of refracturing, we also propose a novel approach to identify refracturing candidates among the old Haynesville wells and deliver another forecast scenario of future refracs. We predict that Haynesville will ultimately produce 30 Tscf of natural gas from the 4684 existing wells. Most likely, by drilling 923 new wells in the core (sweet spot) areas by 2023, EUR will increase to 40 Tscf. Additional 5023 wells in the noncore areas are forecasted to be drilled by 2032, increasing EUR to 90 Tscf. We also show that refracturing old Haynesville wells is more cost-effective than drilling new wells in the poor quality reservoir, especially in the era of low oil and gas prices.
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| (a) A fracture system at Ras Al Khaimah in the United Arab Emirates; (b) Realistic 2D fracture networks with four fracture sets; (c) Realistic 3D fracture networks with four fracture sets. |
31. Wardana Saputra, Wissem Kirati and Tadeusz W. Patzek, "Generalized extreme value statistics, physical scaling and forecasts of gas production in the Haynesville Shale," Journal of Natural Gas Science and Engineering, 2021, 104041, ISSN 1875-5100, https://doi.org/10.1016/j.jngse.2021.104041.
We present a hybrid, data-driven and physics-based method of forecasting play-wide gas production in the Haynesville Shale, which is currently the second-largest shale gas producer in the US. We first define several statistical well cohorts, one for each reservoir quality and each well completion technology in the Haynesville. For each cohort, we use the Generalized Extreme Value (GEV) statistics to obtain the historical average well prototypes. The cumulative production of each well prototype is matched with a physics-based scaling curve, and its production is then extrapolated for up to two more decades. The resulting well prototypes are exceptionally robust. If we replace individual production rates from all existing wells with their corresponding well prototypes and sum them up, the total rate will match remarkably the past gas field rate, and – in this case – we obtain a base or do nothing forecast. Next, we calculate the number of potential infill wells per square mile and schedule future drilling programs to obtain plausible production forecasts in the Haynesville. Because Haynesville is the most active shale play in North America in terms of refracturing, we also propose a novel approach to identify refracturing candidates among the old Haynesville wells and deliver another forecast scenario of future refracs. We predict that Haynesville will ultimately produce 30 Tscf of natural gas from the 4684 existing wells. Most likely, by drilling 923 new wells in the core (sweet spot) areas by 2023, EUR will increase to 40 Tscf. Additional 5023 wells in the noncore areas are forecasted to be drilled by 2032, increasing EUR to 90 Tscf. We also show that refracturing old Haynesville wells is more cost-effective than drilling new wells in the poor quality reservoir, especially in the era of low oil and gas prices.
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