{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T11:42:38Z","timestamp":1776858158298,"version":"3.51.2"},"reference-count":43,"publisher":"SPE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>As major oil and gas companies have been investing in greener energy resources, even though has been part of the oil and gas industry for long time, it has gained its popularity back. Oil and gas industry has adapted to the wind of change and has started investing in and utilizing the technologies significantly. In this perspective, this study investigates and outlines the latest advances, technologies in artificial lift methods as it is applied to unconventionals in a comprehensive manner to serve as an industry-reference for petroleum industry.<\/jats:p>\n               <jats:p>In order to optimize production of oil and gas from unconventional wells, artificial lift (AL) is found to be the most effective method of production. However, as the well passes through its production lifespan, the reservoir pressure declines and artificial lifting of hydrocarbon fluids remains a serious problem. Identifying the best approach, the kind of AL, ideal time and settings to mount the AL as the well passes through its production lifespan is a major challenge. Several investigations have been carried out in the past to identify and establish ground-breaking techniques to improve the application of AL in tight reservoirs. The aim of this study is to conduct a comprehensive review of recent developments in the field of AL and its applications. A review of the application of machine learning (ML) is also presented in this study.<\/jats:p>\n               <jats:p>A comprehensive literature review focusing on the recent developments and findings in artificial lift along with the availability and locations are outlined and discussed under the current dynamics of the oil and gas developments. Literature review includes a broad spectrum that spans from technical petroleum literature with very comprehensive research using onepetro and other databases to other renowned resources including journals and other publications. The information and data are summarized and outlined. This study also provides the techniques on optimziation of artificial lift methods in addition to their comprehensive details with a comparative approach.<\/jats:p>\n               <jats:p>Aritifical lift is a critical component of any oil and gas well especially in unconventionals. The key artificial lift selection and optimziation is through a robust design and established reservoir and well management practices and reflecting the production physics and well dynamics in all aspects. This study outlines the key criteria in the success of aritifical lift applications in individual examples using different methods that will serve for the future decisions as a comprehensive and collective review of all the aspects of the employed techniques and their usability in specific cases.<\/jats:p>\n               <jats:p>Among the few existing studies that explain the methods of aritficial lift are up-to-date and the existing studies within SPE domain focus on certain methods. This study closes the gap and aims to serve as a comprehensive single-source reference for artificial lift and its optimization in unconventionals including all traditional and relatively-new methods.<\/jats:p>","DOI":"10.2118\/201692-ms","type":"proceedings-article","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T19:38:07Z","timestamp":1602704287000},"source":"Crossref","is-referenced-by-count":24,"title":["A Comprehensive Review and Optimization of Artificial Lift Methods in Unconventionals"],"prefix":"10.2118","author":[{"given":"Cenk","family":"Temizel","sequence":"additional","affiliation":[{"name":"Saudi Aramco"}]},{"given":"Celal Hakan","family":"Canbaz","sequence":"additional","affiliation":[{"name":"Ege University"}]},{"given":"Dayanara","family":"Betancourt","sequence":"additional","affiliation":[{"name":"Independent Consultant"}]},{"given":"Ahsen","family":"Ozesen","sequence":"additional","affiliation":[{"name":"TPAO"}]},{"given":"Cagdas","family":"Acar","sequence":"additional","affiliation":[{"name":"Invatare"}]},{"given":"Shanker","family":"Krishna","sequence":"additional","affiliation":[{"name":"Pandit Deendayal Petroleum University"}]},{"given":"Luigi","family":"Saputelli","sequence":"additional","affiliation":[{"name":"ADNOC"}]}],"member":"861","published-online":{"date-parts":[[2020,10,19]]},"reference":[{"key":"2024110719482618700_R1","doi-asserted-by":"crossref","unstructured":"Pankaj, P., Patron, K. 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