Quasi-2D Resistivity Model from Inversion of Vertical Electrical Sounding (VES) Data using Guided Random Search Algorithm

Irawan, Diky; Grandis, Hendra; Sumintadiredja, Prihadi

doi:10.5614/j.math.fund.sci.2015.47.3.5

Jurnal SINTA 1

Quasi-2D Resistivity Model from Inversion of Vertical Electrical Sounding (VES) Data using Guided Random Search Algorithm

Journal of Mathematical and Fundamental Sciences · Vol. 47 No. 3 (2015) · hlm. 269–280

DOI: 10.5614/j.math.fund.sci.2015.47.3.5
ISSN: 2338-5510, 2337-5760
Terbit: 2015-12-01
Penerbit: Directorate for Research and Innovation (DRI) ITB
Bahasa: eng

Abstrak

Vertical electrical sounding (VES) data are usually interpreted in terms of a 1D resistivity model using linearized inversion. The local approach of a non-linear inverse problem has fundamental limitations, i.e. the necessity of a starting model close to the solution and possible convergence to a local rather than a global minimum solution. We studied the application of a global search approach for non-linear inversion using the guided random search method to model VES data. A quasi-2D resistivity model can be created by stitching 1D models obtained from VES data along a profile. Both vertical and lateral resistivity variations are minimized to incorporate a 2D smoothness constraint. The proposed method was applied to invert synthetic VES data as well as field data from a sedimentary environment. Both synthetic and field data inversions resulted in models that correlated well with the known synthetic model and with the geology of the study area, respectively.

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15 penulis · 31 tautan kepenulisan bersama · 8 lintas organisasi

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Bandung Institute of Technology
Badan Geologi
National Research and Innovation Agency
Sumatera Institute of Technology
Institut Teknologi Sepuluh Nopember
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Tampilkan sebagai tabel

Rekan penulis	Organisasi	Artikel bersama
Prihadi Sumintadireja	Bandung Institute of Technology	4
Warsa Warsa	Bandung Institute of Technology	3
Darharta Dahrin	Bandung Institute of Technology	3
Edy Wijanarko	Afiliasi tidak diketahui	3
Ilham Arisbaya	National Research and Innovation Agency	2
Wahyudi Widyatmoko Parnadi	Bandung Institute of Technology	1
Djoko Santoso	Bandung Institute of Technology	1
Accep Handyarso	Badan Geologi	1
Selvi Misnia Irawati	Sumatera Institute of Technology	1
Hidayat Hidayat	Badan Geologi	1
Sungkono Sungkono	Institut Teknologi Sepuluh Nopember	1
Warsa	Afiliasi tidak diketahui	1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jmfs/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.

Metadata asli (oai_dc)

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	<dc:title xml:lang="en-US">Quasi-2D Resistivity Model from Inversion of Vertical Electrical Sounding (VES) Data using Guided Random Search Algorithm</dc:title>
	<dc:creator>Irawan, Diky</dc:creator>
	<dc:creator>Grandis, Hendra</dc:creator>
	<dc:creator>Sumintadiredja, Prihadi</dc:creator>
	<dc:subject xml:lang="en-US">2D model</dc:subject>
	<dc:subject xml:lang="en-US">DC resistivity</dc:subject>
	<dc:subject xml:lang="en-US">global search</dc:subject>
	<dc:subject xml:lang="en-US">Monte Carlo method</dc:subject>
	<dc:subject xml:lang="en-US">non-linear inversion.</dc:subject>
	<dc:description xml:lang="en-US">Vertical electrical sounding (VES) data are usually interpreted in terms of a 1D resistivity model using linearized inversion. The local approach of a non-linear inverse problem has fundamental limitations, i.e. the necessity of a starting model close to the solution and possible convergence to a local rather than a global minimum solution. We studied the application of a global search approach for non-linear inversion using the guided random search method to model VES data. A quasi-2D resistivity model can be created by stitching 1D models obtained from VES data along a profile. Both vertical and lateral resistivity variations are minimized to incorporate a 2D smoothness constraint. The proposed method was applied to invert synthetic VES data as well as field data from a sedimentary environment. Both synthetic and field data inversions resulted in models that correlated well with the known synthetic model and with the geology of the study area, respectively.</dc:description>
	<dc:publisher xml:lang="en-US">Directorate for Research and Innovation (DRI) ITB</dc:publisher>
	<dc:date>2015-12-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jmfs/article/view/1237</dc:identifier>
	<dc:identifier>10.5614/j.math.fund.sci.2015.47.3.5</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Mathematical and Fundamental Sciences; Vol. 47 No. 3 (2015); 269-280</dc:source>
	<dc:source>2338-5510</dc:source>
	<dc:source>2337-5760</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jmfs/article/view/1237/1053</dc:relation>
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