Forskning ved Københavns Universitet - Københavns Universitet


Integrating gradient information with probabilistic traveltime tomography using the Hamiltonian Monte Carlo algorithm

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Seismic traveltime tomography is a popular methodology used to infer the velocity structure of the subsurface (Cerveny, 2001; Nolet, 2008) which has been used across all the scales from near surface imaging to global seismology. In near surface seismology inversion for traveltime is employed to construct velocity models used for further processing of seismic data and crucial to correctly assess deep structures. Formally, the relationship between velocity and traveltime can be described by the eikonal equation (Nolet, 2008), a nonlinear partial differential equation describing the arrival time for a given velocity model as a function of position. Solving numerically the eikonal equation (Vidale, 1988; Podvin and Lecomte, 1991; Rawlinson and Sambridge, 2004) for a given source, provides the traveltime at all grid nodes at once, hence saving a substantial amount of computational time compared to the traditional ray-tracing approach.

Titel80th EAGE Conference and Exhibition 2018 Workshop Programme
UdgivelsesstedCopenhagen, Denmark
ForlagEuropean Association of Geoscientists and Engineers, EAGE
Publikationsdato1 jan. 2018
ISBN (Elektronisk)9789462822573
StatusUdgivet - 1 jan. 2018
Begivenhed80th EAGE Conference and Exhibition 2018 Workshop Programme - Copenhagen, Danmark
Varighed: 10 jun. 201815 jul. 2018


Konference80th EAGE Conference and Exhibition 2018 Workshop Programme
Navn80th EAGE Conference and Exhibition 2018 Workshop Programme

ID: 230792995