{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T19:52:28Z","timestamp":1767383548688,"version":"3.37.3"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T00:00:00Z","timestamp":1658275200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T00:00:00Z","timestamp":1658275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Natural Science Foundation","award":["42002307"],"award-info":[{"award-number":["42002307"]}]},{"name":"National Key Research and Development Program of China","award":["2018YFC0603405"],"award-info":[{"award-number":["2018YFC0603405"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Arab J Sci Eng"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1007\/s13369-022-07103-x","type":"journal-article","created":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T05:02:58Z","timestamp":1658293378000},"page":"9069-9084","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Optimization of Drilling Parameters of Target Wells Based on Machine Learning and Data Analysis"],"prefix":"10.1007","volume":"48","author":[{"given":"Zhiyuan","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3598-5351","authenticated-orcid":false,"given":"Yongsheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xing","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijun","family":"Dou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gansheng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianguo","family":"Lv","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanbiao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,20]]},"reference":[{"key":"7103_CR1","doi-asserted-by":"publisher","DOI":"10.2118\/1349-G","author":"JW Graham","year":"1959","unstructured":"Graham, J.W.; Muench, N.L.: Analytical determination of optimum bit weight and rotary speed combinations. J. Pet. Technol. (1959). https:\/\/doi.org\/10.2118\/1349-G","journal-title":"J. Pet. Technol."},{"key":"7103_CR2","doi-asserted-by":"publisher","unstructured":"Eren, T., Ozbayoglu, M.E.: Real time optimization of drilling parameters during drilling operations. In: Spe Oil & Gas India Conference & Exhibition. (2010) https:\/\/doi.org\/10.2118\/129126-MS","DOI":"10.2118\/129126-MS"},{"issue":"10","key":"7103_CR3","doi-asserted-by":"publisher","first-page":"45","DOI":"10.2118\/2008-132","volume":"49","author":"HR Motahhari","year":"2010","unstructured":"Motahhari, H.R.; Hareland, G.; James, J.A.: Improved drilling efficiency technique using integrated PDM and PDC bit parameters. J. Can. Pet. Technol. 49(10), 45\u201352 (2010). https:\/\/doi.org\/10.2118\/2008-132","journal-title":"J. Can. Pet. Technol."},{"issue":"2","key":"7103_CR4","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/0148-9062(65)90022-7","volume":"2","author":"R Teale","year":"1965","unstructured":"Teale, R.: The concept of specific energy in rock drilling. Int. J. Rock Mech. Min. Sci. Geomech. Abstr. 2(2), 57\u201373 (1965). https:\/\/doi.org\/10.1016\/0148-9062(65)90022-7","journal-title":"Int. J. Rock Mech. Min. Sci. Geomech. Abstr."},{"key":"7103_CR5","doi-asserted-by":"publisher","unstructured":"Dupriest, F.E., Koederitz, W.L.: Maximizing drill rates with real-time surveillance of mechanical specific energy. In: SPE\/IADC drilling conference. (2005): OnePetro. https:\/\/doi.org\/10.2118\/92194-MS","DOI":"10.2118\/92194-MS"},{"key":"7103_CR6","doi-asserted-by":"publisher","DOI":"10.1115\/1.4033067","author":"A Nascimento","year":"2016","unstructured":"Nascimento, A.; Elmgerbi, A.; Roohi, A.; Prohaska, M.; Thonhauser, G.; Gon\u00e7alves, J.L.; Mathias, M.H.: Reverse engineering: a new well monitoring and analysis methodology approaching playing-back drill-rate tests in real-time for drilling optimization. J. Energy Res. Technol. (2016). https:\/\/doi.org\/10.1115\/1.4033067","journal-title":"J. Energy Res. Technol."},{"key":"7103_CR7","unstructured":"Bingham, M.G.: A new approach to interpreting-- rock drillability. (1965)"},{"issue":"04","key":"7103_CR8","doi-asserted-by":"publisher","first-page":"541","DOI":"10.2118\/1520-PA","volume":"19","author":"JR Eckel","year":"1967","unstructured":"Eckel, J.R.: Microbit studies of the effect of fluid properties and hydraulics on drilling rate. J. Petrol. Technol. 19(04), 541\u2013546 (1967). https:\/\/doi.org\/10.2118\/1520-PA","journal-title":"J. Petrol. Technol."},{"issue":"04","key":"7103_CR9","doi-asserted-by":"publisher","first-page":"371","DOI":"10.2118\/4238-PA","volume":"14","author":"AT Bourgoyne","year":"1974","unstructured":"Bourgoyne, A.T.; Young, F.S.: A multiple regression approach to optimal drilling and abnormal pressure detection. Soc. Pet. Eng. J. 14(04), 371\u2013384 (1974). https:\/\/doi.org\/10.2118\/4238-PA","journal-title":"Soc. Pet. Eng. J."},{"issue":"01","key":"7103_CR10","doi-asserted-by":"publisher","first-page":"9","DOI":"10.2118\/13259-PA","volume":"2","author":"TM Warren","year":"1987","unstructured":"Warren, T.M.: Penetration rate performance of roller cone bits. SPE Drill. Eng. 2(01), 9\u201318 (1987). https:\/\/doi.org\/10.2118\/13259-PA","journal-title":"SPE Drill. Eng."},{"key":"7103_CR11","doi-asserted-by":"publisher","DOI":"10.2118\/26957-MS","author":"G Hareland","year":"1994","unstructured":"Hareland, G.; Rampersad, P.R.: Drag-Bit Model Including. Wear (1994). https:\/\/doi.org\/10.2118\/26957-MS","journal-title":"Wear"},{"key":"7103_CR12","doi-asserted-by":"publisher","DOI":"10.2118\/202481-PA","author":"D Etesami","year":"2020","unstructured":"Etesami, D.; Shirangi, M.G.; Zhang, W.J.: A semiempirical model for rate of penetration with application to an offshore gas field. SPE Drill. Complet. (2020). https:\/\/doi.org\/10.2118\/202481-PA","journal-title":"SPE Drill. Complet."},{"key":"7103_CR13","doi-asserted-by":"publisher","unstructured":"AlArfaj, I.; Khoukhi, A.; Eren, T. Application of advanced computational intelligence to rate of penetration prediction. In: 2012 IEEE https:\/\/doi.org\/10.1109\/EMS.2012.79","DOI":"10.1109\/EMS.2012.79"},{"key":"7103_CR14","doi-asserted-by":"publisher","unstructured":"Amar, K.; Ibrahim, A.: Rate of penetration prediction and optimization using advances in artificial neural networks, a comparative study. https:\/\/doi.org\/10.5220\/0004172506470652 (2012)","DOI":"10.5220\/0004172506470652"},{"key":"7103_CR15","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.petrol.2017.09.020","volume":"159","author":"C Hegde","year":"2017","unstructured":"Hegde, C.; Daigle, H.; Millwater, H.; Gray, K.: Analysis of rate of penetration (ROP) prediction in drilling using physics-based and data-driven models. J. Pet. Sci. Eng. 159, 295\u2013306 (2017). https:\/\/doi.org\/10.1016\/j.petrol.2017.09.020","journal-title":"J. Pet. Sci. Eng."},{"key":"7103_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.jngse.2016.03.057","author":"MK Moraveji","year":"2016","unstructured":"Moraveji, M.K.; Naderi, M.: Drilling rate of penetration prediction and optimization using response surface methodology and bat algorithm. J. Nat. Gas Sci. Eng. (2016). https:\/\/doi.org\/10.1016\/j.jngse.2016.03.057","journal-title":"J. Nat. Gas Sci. Eng."},{"key":"7103_CR17","doi-asserted-by":"publisher","unstructured":"Hegde, C., Wallace, S., Gray, K.: Using trees, bagging, and random forests to predict rate of penetration during drilling. In: Society of Petroleum Engineers. SPE-176792-MS. Abu Dhabi. p. 1\u201312. https:\/\/doi.org\/10.2118\/176792-MS (2015)","DOI":"10.2118\/176792-MS"},{"key":"7103_CR18","doi-asserted-by":"publisher","unstructured":"Hegde, C.M., Wallace, S.P., Gray, K.E.: Use of regression and bootstrapping in drilling inference and prediction. In: Society of Petroleum Engineers. SPE-176791-MS. 2015: Abu Dhabi, UAE. p. 1\u201311. https:\/\/doi.org\/10.2118\/176791-MS","DOI":"10.2118\/176791-MS"},{"key":"7103_CR19","doi-asserted-by":"publisher","unstructured":"Noshi, C.I., Schubert, J.J.: Application of data science and machine learning algorithms for rop prediction: turning data into knowledge. https:\/\/doi.org\/10.2118\/191823-18ERM-MS (2019)","DOI":"10.2118\/191823-18ERM-MS"},{"key":"7103_CR20","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.jngse.2017.02.019","volume":"40","author":"C Hegde","year":"2017","unstructured":"Hegde, C.; Gray, K.E.: Use of machine learning and data analytics to increase drilling efficiency for nearby wells. J. Nat. Gas Sci. Eng. 40, 327\u2013335 (2017). https:\/\/doi.org\/10.1016\/j.jngse.2017.02.019","journal-title":"J. Nat. Gas Sci. Eng."},{"key":"7103_CR21","doi-asserted-by":"publisher","unstructured":"Li, Y., Samuel, R.: Prediction of penetration rate ahead of the bit through real-time updated machine learning models. In: SPE\/IADC.SPE\/IADC-194105-MS. The Hague, The Netherlands. https:\/\/doi.org\/10.2118\/194105-MS (2019)","DOI":"10.2118\/194105-MS"},{"key":"7103_CR22","doi-asserted-by":"publisher","unstructured":"Mantha, B., Samuel, R.: ROP optimization using artificial intelligence techniques with statistical regression coupling. https:\/\/doi.org\/10.2118\/181382-MS(2016)","DOI":"10.2118\/181382-MS"},{"key":"7103_CR23","doi-asserted-by":"publisher","unstructured":"Valisevich, A., Lukoil-Nizhnevolzhskneft., PhD, A.R., Bebeshko, I., Moreno, R., Zhentichka, M., Bits, S.: Drillbit optimization system: real-time approach to enhance rate of penetration and bit wear monitoring. In: Society of Petroleum Engineers.SPE-176517-MS. Moscow, Russia. https:\/\/doi.org\/10.2118\/176517-ms (2015)","DOI":"10.2118\/176517-ms"},{"key":"7103_CR24","doi-asserted-by":"publisher","unstructured":"Amer, M.M., DAHAB, A.S., Hashem, A.A.: An ROP predictive model in nile delta area using artificial neural networks. In: Society of Petroleum Engineers.SPE-187969-MS: Dammam, Saudi Arabia. https:\/\/doi.org\/10.2118\/187969-MS (2017)","DOI":"10.2118\/187969-MS"},{"key":"7103_CR25","doi-asserted-by":"publisher","unstructured":"Hegde, C., Wallace, S., Gray, K.: Real time prediction and classification of torque and drag during drilling using statistical learning methods. In: Society of Petroleum Engineers.SPE-177313-MS: Morgantown, West Virginia, USA. https:\/\/doi.org\/10.2118\/177313-MS (2015)","DOI":"10.2118\/177313-MS"},{"key":"7103_CR26","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1016\/j.jngse.2018.06.006","volume":"56","author":"C Hegde","year":"2018","unstructured":"Hegde, C.; Gray, K.: Evaluation of coupled machine learning models for drilling optimization. J.Nat. Gas Sci. Eng. 56, 397\u2013407 (2018). https:\/\/doi.org\/10.1016\/j.jngse.2018.06.006","journal-title":"J.Nat. Gas Sci. Eng."},{"issue":"6527","key":"7103_CR27","doi-asserted-by":"publisher","first-page":"108075","DOI":"10.1016\/j.petrol.2020.108075","volume":"200","author":"S Ravela","year":"2020","unstructured":"Ravela, S.; Alali, A.M.; Abughaban, M.F.; Aman, B.M.: Hybrid data driven drilling and rate of penetration optimization. J. Pet. Sci. Eng. 200(6527), 108075 (2020). https:\/\/doi.org\/10.1016\/j.petrol.2020.108075","journal-title":"J. Pet. Sci. Eng."},{"key":"7103_CR28","unstructured":"Qi, M.: LightGBM: a highly efficient gradient boosting decision tree. in neural information processing systems. https:\/\/www.jstor.org\/stable\/2699986 (2018)"},{"issue":"5","key":"7103_CR29","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"J Friedman","year":"2001","unstructured":"Friedman, J.: Greedy function approximation\u202f: a gradient boosting machine. Ann. Stat. 29(5), 1189\u20131232 (2001)","journal-title":"Ann. Stat."},{"issue":"11","key":"7103_CR30","doi-asserted-by":"publisher","first-page":"8221","DOI":"10.1007\/s13369-014-1376-0","volume":"39","author":"X Chen","year":"2014","unstructured":"Chen, X.; Fan, H.; Guo, B.; Gao, D.; Wei, H.; Ye, Z.: Real-time prediction and optimization of drilling performance based on a new mechanical specific energy model. Arab. J. Sci. Eng. 39(11), 8221\u20138231 (2014). https:\/\/doi.org\/10.1007\/s13369-014-1376-0","journal-title":"Arab. J. Sci. Eng."},{"key":"7103_CR31","doi-asserted-by":"publisher","unstructured":"Armenta, M. Identifying inefficient drilling conditions using drilling-specific energy. In: SPE Annual Technical Conference and Exhibition. OnePetro. https:\/\/doi.org\/10.2118\/116667-MS (2008)","DOI":"10.2118\/116667-MS"},{"issue":"3","key":"7103_CR32","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1080\/0952813X.2016.1198936","volume":"29","author":"F Anifowose","year":"2017","unstructured":"Anifowose, F.; Khoukhi, A.; Abdulraheem, A.: Investigating the effect of training-testing data stratification on the performance of soft computing techniques: an experimental study. J. Exp. Theor. Artif. Intell. 29(3), 517\u2013535 (2017). https:\/\/doi.org\/10.1080\/0952813X.2016.1198936","journal-title":"J. Exp. Theor. Artif. Intell."},{"issue":"5","key":"7103_CR33","doi-asserted-by":"publisher","first-page":"1706","DOI":"10.2118\/191141-PA","volume":"23","author":"C Hegde","year":"2018","unstructured":"Hegde, C.; Daigle, H.; Gray, K.E.: Performance comparison of algorithms for real-time rate-of-penetration optimization in drilling using data-driven models. SPE J. 23(5), 1706\u20131722 (2018)","journal-title":"SPE J."},{"key":"7103_CR34","doi-asserted-by":"publisher","unstructured":"Dupriest, F.: Comprehensive drill-rate management process to maximize rate of penetration. In: SPE Annual Technical Conference and Exhibition. https:\/\/doi.org\/10.2118\/191141-PA (2006)","DOI":"10.2118\/191141-PA"},{"key":"7103_CR35","doi-asserted-by":"publisher","first-page":"108991","DOI":"10.1016\/j.petrol.2021.108991","volume":"206","author":"V Ramba","year":"2021","unstructured":"Ramba, V.; Selvaraju, S.; Subbiah, S.; Palanisamy, M.; Srivastava, A.: Optimization of drilling parameters using improved play-back methodology. J. Pet. Sci. Eng. 206, 108991 (2021). https:\/\/doi.org\/10.1016\/j.petrol.2021.108991","journal-title":"J. Pet. Sci. Eng."}],"container-title":["Arabian Journal for Science and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13369-022-07103-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13369-022-07103-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13369-022-07103-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T05:12:20Z","timestamp":1687237940000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13369-022-07103-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,20]]},"references-count":35,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["7103"],"URL":"https:\/\/doi.org\/10.1007\/s13369-022-07103-x","relation":{},"ISSN":["2193-567X","2191-4281"],"issn-type":[{"type":"print","value":"2193-567X"},{"type":"electronic","value":"2191-4281"}],"subject":[],"published":{"date-parts":[[2022,7,20]]},"assertion":[{"value":"21 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}