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dc.contributor.authorSaputra, Wardana
dc.contributor.authorKirati, Wissem
dc.contributor.authorPatzek, Tadeusz
dc.date.accessioned2019-10-07T07:45:05Z
dc.date.available2019-10-07T07:45:05Z
dc.date.issued2019-09-24
dc.identifier.citationSaputra, W., Kirati, W., & Patzek, T. (2019). Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale. Energies, 12(19), 3641. doi:10.3390/en12193641
dc.identifier.doi10.3390/en12193641
dc.identifier.doi10.1021/acs.energyfuels.9b01385
dc.identifier.doi10.26434/chemrxiv.8326898
dc.identifier.doi10.1016/j.jngse.2021.104041
dc.identifier.urihttp://hdl.handle.net/10754/656925
dc.description.abstractWe 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 P50, P10, 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.
dc.description.sponsorshipWardana Saputra (PhD student) was supported by baseline research funding from KAUST to Tad Patzek. Wissem Kirati (Research Engineer) was supported by the Division of Computer, Electrical and Mathematical Science at KAUST. The authors thank the Ali I. Al-Naimi Petroleum Engineering Research Center (ANPERC) at KAUST for supporting this research. We thank the reviewers for their thorough, informative and timely reviews.
dc.publisherMDPI AG
dc.relation.isversionofDOI:10.20944/preprints201908.0195.v1
dc.relation.urlhttps://www.mdpi.com/1996-1073/12/19/3641
dc.rightscopyright 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectEUR
dc.subjectinfill wells
dc.subject(re)fracturing
dc.subjectpressure depletion
dc.titleGeneralized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale
dc.typeArticle
dc.contributor.departmentAli I. Al-Naimi Petroleum Engineering Research Center (ANPERC)
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentEnergy Resources and Petroleum Engineering
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalEnergies
dc.eprint.versionPublisher's Version/PDF
kaust.personSaputra, Wardana
kaust.personKirati, Wissem
kaust.personPatzek, Tadeusz
refterms.dateFOA2019-10-07T07:45:38Z
kaust.acknowledged.supportUnitAli I. Al-Naimi Petroleum Engineering Research Center


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copyright 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as copyright 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).