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APG: A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies

Geoscience Frontiers 2021年第6期12卷 90-104页

作者： Seyed amir naghibi Hossein Hashemi Biswajeet Pradhan Department of Water Resources Engineering&Center for Advanced Middle Eastern Studies Lund UniversityLundSweden Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) Faculty of Engineering and Information TechnologyUniversity of Technology SydneyNew South WalesAustralia Department of Energy and Mineral Resources Engineering Sejong UniversityChoongmu-gwan209 Neungdong-ro Gwangjin-guSeoul 05006Republic of Korea Department of Meteorology King Abdulaziz UniversityP.O.Box 80234Jeddah 21589Saudi Arabia Earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaBangiSelangorMalaysia

One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of *** solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial *** APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are *** test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)*** BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker performances with the SAS and Random *** effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7%from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4%from the SAS dataset,*** APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental binary *** proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.

关键词： Absence-dataset Classification Python Machine learning algorithms GIS Groundwater Hydrogeology

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Prediction of new perforation intervals in a depleted reservoir to achieve the maximum productivity: A case study of PNN logging in a cased-well of an Iranian oil reservoir

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Petroleum 2020年第2期6卷 170-176页

作者： Saeed Zaker Shahab mohamadi nafchi Mahdi Rastegarnia Soheila Bagheri Ali Sanati amir naghibi Islamic Azad University Science and Research BranchTehranIran Islamic Azad University Central BranchTehranIran Head of Petrophysics Section Petro Pardazesh Aria CompanyTehranIran Senior Petrophysicist OTS CompanyTehranIran School of Petrochemical and Petroleum Engineering Hakim Sabzevari UniversitySabzevarIran Senior Petrophysicist Iranian Central Oil Field CompanyTehranIran

Pulsed neutron-neutron(PNN)logging is based on emitting neutrons into the near-wellbore zone and computing the neutron count decay due to scattering and *** main application of this logging tool is to determine the current oil saturation and to detect channeling in perforated and non-perforated intervals behind the *** interpretation of the results obtained from PNN logging enables engineers to predict new perforation intervals in depleted *** study examines the application of PNN logging in a well located in one of Iranian oil *** interpretation procedure is described step by *** principle of the PNN logging and the specifications of the tool are discussed and the applications of PNN logging in evaluation of oil saturation,identification of water flooded zones and prediction of potential perforating zones are *** is also investigated between all layers,good and poor oil zones are characterized based on the calculated oil saturations and new perforation intervals are suggested with the aim to boost oil production from the *** results of this study show that zones 1 to 5 having low oil saturations,are interpreted as depleted oil *** 6 to 8 are interpreted as good oil zones having high potential to produce *** 9 is interpreted as a water zone.

关键词： Pulse neutron-neutron(PNN)logging Sigma value Remaining oil saturation Conventional logging Perforation intervals Depleted reservoir

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