Numerical Modeling of Marine Seismology in the Arctic Region During Deposit Dissolution due to Oil Migration

As the Arctic region requires costly and difficult to access surveys of the ground, numerical modeling proves to be an effective way to study occurring processes in the area. Moreover, the simulations of the seismic exploration can help identify the main signs of oil migration which is crucial for the risk assessment of the deposit development. Therefore, the main goal of this work is to conduct the forward modeling of the seismology in the offshore areas of the region in order to determine the indicators of such processes. The present study, in particular, is aimed at recreating of basic features of the region such as a layered ground with the gradual change in material parameters and inclusion of a permafrost sheet. Furthermore, the boundaries between layers are considered to be curvilinear. This complex problem was effectively solved using the gridcharacteristic method which allows for the accelerating of the calculations using OpenMP. As a result of the computations, the reconstructed wave phenomena is analyzed based on the obtained wave patterns and synthesized seismograms. The change in the responses from the oil reservoir in the process of draining is identified which can further help interpret real measurements.

Institutions

Publication Details

Journal
Supercomputing Frontiers and Innovations
Published
2024-11-01
DOI
https://doi.org/10.14529/jsfi240403
Citations
1
Primary Topic
Geological Studies and Exploration
Type
article
Field-Weighted Citation Impact
0.83
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Numerical Modeling of Marine Seismology in the Arctic Region During Deposit Dissolution due to Oil Migration

1 citations
Supercomputing Frontiers and Innovations
Geological Studies and Exploration
0.83
article

Numerical Modeling of Marine Seismology in the Arctic Region During Deposit Dissolution due to Oil Migration

article en
1 citations

Abstract

As the Arctic region requires costly and difficult to access surveys of the ground, numerical modeling proves to be an effective way to study occurring processes in the area. Moreover, the simulations of the seismic exploration can help identify the main signs of oil migration which is crucial for the risk assessment of the deposit development. Therefore, the main goal of this work is to conduct the forward modeling of the seismology in the offshore areas of the region in order to determine the indicators of such processes. The present study, in particular, is aimed at recreating of basic features of the region such as a layered ground with the gradual change in material parameters and inclusion of a permafrost sheet. Furthermore, the boundaries between layers are considered to be curvilinear. This complex problem was effectively solved using the gridcharacteristic method which allows for the accelerating of the calculations using OpenMP. As a result of the computations, the reconstructed wave phenomena is analyzed based on the obtained wave patterns and synthesized seismograms. The change in the responses from the oil reservoir in the process of draining is identified which can further help interpret real measurements.

Supercomputing Frontiers and InnovationsVol. 11(4)
Moscow Institute of Physics and Technology (RU)
Life below water
Openalex Percentile: Top 17%
Geological Studies and Exploration
0.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Numerical Modeling of Marine Seismology in the Arctic Region During Deposit Dissolution due to Oil Migration · Supercomputing Frontiers and Innovations (2024) | TGRS Research Map | TGRS