LEADER 00642nas 2200253 450 001 000012197 005 20080603131844.0 011 $a0391-7444 100 $a20080603b19701985km-y0itay50------ba 101 0 $aita 102 $aIT 110 $aaia----0--- 200 1 $aData report$fSiemens Data 210 $aMilano$cSiemens S.p.A.$d1970-1985 215 $afascicoli 326 $aQuadrimestrale 440 0$1001000012201 610 1 $aInformatica 712 02$aSiemens Data 801 0$aIT$bUNIPARTHENOPE$gRICA$2UNIMARC 912 $a000012197 958 $a1977-1979; 1981-1985$cPIST 996 $aData report$9974749 997 $aUNIPARTHENOPE LEADER 02958nam 2200481 450 001 9910484054903321 005 20220505234456.0 010 $a3-030-71768-2 024 7 $a10.1007/978-3-030-71768-1 035 $a(CKB)4100000011912018 035 $a(DE-He213)978-3-030-71768-1 035 $a(MiAaPQ)EBC6587710 035 $a(Au-PeEL)EBL6587710 035 $a(OCoLC)1250085222 035 $a(PPN)255885008 035 $a(EXLCZ)994100000011912018 100 $a20220113d2021 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA primer on machine learning in subsurface geosciences /$fShuvajit Bhattacharya 205 $a1st ed. 2021. 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (XVII, 172 p. 130 illus., 118 illus. in color.) 225 1 $aSpringerBriefs in Petroleum Geoscience & Engineering,$x2509-3126 311 $a3-030-71767-4 327 $aIntroduction -- Brief Review of Statistical Measures -- Basic Steps in Machine Learning and Deep Learning Models -- Brief Review of Popular Machine Learning and Deep Learning Algorithms -- Applications of ML/DL in Geophysics and Petrophysics Domain -- Applications of ML/DL in Geology Domain -- Multi-scale Data Integration and Analytics -- The Road Ahead. 330 $aThis book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences. . 410 0$aSpringerBriefs in Petroleum Geoscience & Engineering,$x2509-3126 606 $aGeology$xData processing 615 0$aGeology$xData processing. 676 $a550.285 700 $aBhattacharya$b Shuvajit$0866391 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484054903321 996 $aA Primer on Machine Learning in Subsurface Geosciences$91933722 997 $aUNINA LEADER 01781nas 2200529-a 450 001 996335853403316 005 20240112213020.0 011 $a2332-1601 035 $a(OCoLC)48672567 035 $a(CKB)111022869251006 035 $a(CONSER)--2004230164 035 $a(EXLCZ)99111022869251006 100 $a20011228b19uu2020 -a- a 101 0 $aeng 135 $aurmnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aChiefs of State and Cabinet members of foreign governments 210 $a[Washington, D.C.] $cCIA Directorate of Intelligence 311 $a0162-2951 517 1 $aChiefs of State & Cabinet members of foreign governments, a directory 517 1 $aChiefs of State & Cabinet members of foreign governments 517 1 $aWorld leaders and cabinet members of foreign governments 606 $aHeads of state$vRegisters 606 $aCabinet officers$vRegisters 606 $aCabinet officers$2fast$3(OCoLC)fst00843535 606 $aHeads of state$2fast$3(OCoLC)fst00952677 606 $aCABINET OFFICERS$2unbist 606 $aDIRECTORIES$2unbist 606 $aHEADS OF STATE$2unbist 608 $aPeriodicals.$2fast 608 $aRegisters (Lists)$2fast 608 $aRegisters (Lists)$2lcgft 615 0$aHeads of state 615 0$aCabinet officers 615 7$aCabinet officers. 615 7$aHeads of state. 615 17$aCABINET OFFICERS. 615 17$aDIRECTORIES. 615 17$aHEADS OF STATE. 676 $a320 712 02$aUnited States.$bCentral Intelligence Agency.$bDirectorate of Intelligence. 906 $aJOURNAL 912 $a996335853403316 996 $aChiefs of State and Cabinet members of foreign governments$92388852 997 $aUNISA