On Seismic Monitoring Of Dynamic Overpressure Zones In Shallow Marine Sediments

The paper presents an algorithm for reconstruction of stress state parameters of rock massif based on data on natural fractures. For one well developing an oil field, the directions of the principal in-situ stresses, their relative magnitudes, and the strength of the rocks in the near-wellbore space were reconstructed. Stress inversion results are in agreement with other methods of stress estimation, in particular, with the results of the mini-hydraulic fracture test. The inverse problem of stress state estimation is solved using the Monte Carlo method. An algorithm of applying the apparatus of mathematical statistics - the method of moments for determining distribution parameters from the Pearson distribution family - to quantify the ambiguity of the estimation of the directions of the principal stresses and their relative magnitudes is presented. The proposed algorithm can be used for independent reconstruction of stresses for carbonate rocks, provided that there is information about the conductivity of fractures in the rocks of the near-wellbore space to further improve the quality of one-dimensional and three-dimensional geomechanical modelling.

Authors

Publication Details

Journal
Rossijskij žurnal nauk o zemle/Russian journal of earth sciences
Published
2024-12-16
DOI
https://doi.org/10.2205/2024es000958
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On Seismic Monitoring Of Dynamic Overpressure Zones In Shallow Marine Sediments

Irina O. Bayuk, Sergey Vladimirovich Fomichev, S. A. Tikhotskiy, N. V. Dubinya et al.
Rossijskij žurnal nauk o zemle/Russian journal of earth sciences
Seismic Imaging and Inversion Techniques
article

On Seismic Monitoring Of Dynamic Overpressure Zones In Shallow Marine Sediments

Irina O. Bayuk, Sergey Vladimirovich Fomichev, S. A. Tikhotskiy, N. V. Dubinya, D. Kuprin, I. Voronov
article en

Abstract

The paper presents an algorithm for reconstruction of stress state parameters of rock massif based on data on natural fractures. For one well developing an oil field, the directions of the principal in-situ stresses, their relative magnitudes, and the strength of the rocks in the near-wellbore space were reconstructed. Stress inversion results are in agreement with other methods of stress estimation, in particular, with the results of the mini-hydraulic fracture test. The inverse problem of stress state estimation is solved using the Monte Carlo method. An algorithm of applying the apparatus of mathematical statistics - the method of moments for determining distribution parameters from the Pearson distribution family - to quantify the ambiguity of the estimation of the directions of the principal stresses and their relative magnitudes is presented. The proposed algorithm can be used for independent reconstruction of stresses for carbonate rocks, provided that there is information about the conductivity of fractures in the rocks of the near-wellbore space to further improve the quality of one-dimensional and three-dimensional geomechanical modelling.

Rossijskij žurnal nauk o zemle/Russian journal of earth sciences
Openalex Percentile: Top 77%
Seismic Imaging and Inversion Techniques
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.

On Seismic Monitoring Of Dynamic Overpressure Zones In Shallow Marine Sediments — Irina O. Bayuk, Sergey Vladimirovich Fomichev, et al. · Rossijskij žurnal nauk o zemle/Russian journal of earth sciences (2024) | TGRS Research Map | TGRS