LEADER 01104nam0-2200361li-450 001 990000245590203316 005 20180312154819.0 010 $a0-8053-0910-1 035 $a0024559 035 $aUSA010024559 035 $a(ALEPH)000024559USA01 035 $a0024559 100 $a20001109d1989----km-y0itay0103----ba 101 0 $aeng 102 $aUS 200 1 $aC ++ for C programmers$fIra Pohl 210 $aRedwood City (Calif.) [etc.]$cBenjamin/Cummings$dcopyr. 1989 215 $aXII, 244 p.$cill.$d24 cm 610 1 $alinguaggio c++ 676 $a005133$9Specifici linguaggi di programmazione 700 1$aPohl,$bIra$042372 801 $aSistema bibliotecario di Ateneo dell' Università di Salerno$gRICA 912 $a990000245590203316 951 $a005.133 POH (A)$b0011641$c005.133$d00103268 959 $aBK 969 $aSCI 979 $c19950109 979 $c20001110$lUSA01$h1715 979 $aALANDI$b90$c20010321$lUSA01$h1253 979 $c20020403$lUSA01$h1632 979 $aPATRY$b90$c20040406$lUSA01$h1618 996 $aC ++ for C programmers$91502338 997 $aUNISA LEADER 04071nam 22007575 450 001 9910918696403321 005 20241219115236.0 010 $a9783031757457 010 $a3031757459 024 7 $a10.1007/978-3-031-75745-7 035 $a(CKB)37054911900041 035 $a(MiAaPQ)EBC31851876 035 $a(Au-PeEL)EBL31851876 035 $a(DE-He213)978-3-031-75745-7 035 $a(OCoLC)1484076315 035 $a(EXLCZ)9937054911900041 100 $a20241219d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Learning for Seismic Data Enhancement and Representation /$fby Shirui Wang, Wenyi Hu, Xuqing Wu, Jiefu Chen 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (164 pages) 225 1 $aAdvances in Oil and Gas Exploration & Production,$x2509-3738 311 08$a9783031757440 311 08$a3031757440 327 $aChapter 1: Introduction -- Chapter 2: Full Waveform Inversion With Low-Frequency Extrapolation -- 3: Deep Learning For Seismic Deblending -- Chapter 4: Blind-Trace Network For Self-Supervised Seismic Data Interpolation -- Chapter 5: Self-Supervised Learning For Anti-Aliased Seismic Data Interpolation Using Dip Information -- Chapter 6:Deep Learning For Seismic Data Compression -- Chapter 7: Conclusion. 330 $aSeismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns various factors such as acquisition design, environmental constraints, sampling resolution, and noises. The focus of this book is to investigate efficient seismic data representation and signal enhancement solutions by leveraging the powerful feature engineering capability of deep learning. The book delves into seismic data representation and enhancement issues, ranging from seismic acquisition design to subsequent quality improvement and compression technologies. Given the challenges of obtaining suitable labeled training datasets for seismic data processing problems, we concentrate on exploring deep learning approaches that eliminate the need for labels. We combined novel deep learning techniques with conventional seismic data processing methods, and construct networks and frameworks tailored for seismic data processing. The editors and authors of this book come from both academia and industry with hands-on experiences in seismic data processing and imaging. 410 0$aAdvances in Oil and Gas Exploration & Production,$x2509-3738 606 $aGeophysics 606 $aData mining 606 $aElectrical engineering 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aArtificial intelligence$xData processing 606 $aGeophysics 606 $aData Mining and Knowledge Discovery 606 $aElectrical and Electronic Engineering 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aData Science 615 0$aGeophysics. 615 0$aData mining. 615 0$aElectrical engineering. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aArtificial intelligence$xData processing. 615 14$aGeophysics. 615 24$aData Mining and Knowledge Discovery. 615 24$aElectrical and Electronic Engineering. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aData Science. 676 $a550 700 $aWang$b Shirui$0635487 701 $aHu$b Wenyi$01781186 701 $aWu$b Xuqing$01781187 701 $aChen$b Jiefu$0855618 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910918696403321 996 $aDeep Learning for Seismic Data Enhancement and Representation$94305950 997 $aUNINA