Background <p>Fault analysis is a central aspect of gravity exploration,providing vital insights into subsurface geology for resource exploration andmanagement. This study introduces a novel inversion technique tailored for theinterpretation of gravitational responses stemming from subsurface faults.Leveraging techniques like local wavenumber (LWN) and imaging indicator, the methodextracts pertinent insights. Central to the methodology is the computation ofthe rank indicator (β) through the comparison of local wavenumbers betweenobserved and estimated gravitational fields.</p> Results <p>Identifying the maximum rank indicator (β<sub>max</sub>) is crucialas it signifies the optimal true target parameters. Rigorous validation isperformed across two synthetic scenarios encompassing noisy, and multi-faultanomalies, Moreover, practical deployment on two distinct real datasets from geologicalhazards and hydrocarbon exploration endeavors in Egypt and USA underscores itseffectiveness.</p> Conclusion <p>The method demonstrates versatility across diverse contexts, highprecision, and a notable ability to operate without requiring prior knowledgeof the source shape. These capabilities are further validated against boreholedata and existing literature. This study introduces a novel inversion technique tailored for the interpretation of gravitational responses stemming from subsurface faults. Leveraging techniques like local wavenumber (LWN) and imaging indicator, the method extracts pertinent insights. Central to the methodology is the computation of the rank indicator (β) through the comparison of local wavenumbers between observed and estimated gravitational fields. Identifying the maximum rank indicator (β<sub>max</sub>) is crucial as it signifies the optimal true target parameters. Rigorous validation is performed across two synthetic scenarios encompassing noisy, and multi-fault anomalies, affirming the approach's efficacy. Moreover, practical deployment on two distinct real datasets from geological hazards and hydrocarbon exploration endeavors in Egypt and USA underscores its effectiveness, versatility across diverse contexts, precision, and notable ability to operate sans prior knowledge of source shape, validated against borehole data and existing literature.</p>

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An advanced imaging scheme for fault structures utilizing gravity rank indicator

  • Zein E. Diab,
  • Mahmoud Elhussein

摘要

Background

Fault analysis is a central aspect of gravity exploration,providing vital insights into subsurface geology for resource exploration andmanagement. This study introduces a novel inversion technique tailored for theinterpretation of gravitational responses stemming from subsurface faults.Leveraging techniques like local wavenumber (LWN) and imaging indicator, the methodextracts pertinent insights. Central to the methodology is the computation ofthe rank indicator (β) through the comparison of local wavenumbers betweenobserved and estimated gravitational fields.

Results

Identifying the maximum rank indicator (βmax) is crucialas it signifies the optimal true target parameters. Rigorous validation isperformed across two synthetic scenarios encompassing noisy, and multi-faultanomalies, Moreover, practical deployment on two distinct real datasets from geologicalhazards and hydrocarbon exploration endeavors in Egypt and USA underscores itseffectiveness.

Conclusion

The method demonstrates versatility across diverse contexts, highprecision, and a notable ability to operate without requiring prior knowledgeof the source shape. These capabilities are further validated against boreholedata and existing literature. This study introduces a novel inversion technique tailored for the interpretation of gravitational responses stemming from subsurface faults. Leveraging techniques like local wavenumber (LWN) and imaging indicator, the method extracts pertinent insights. Central to the methodology is the computation of the rank indicator (β) through the comparison of local wavenumbers between observed and estimated gravitational fields. Identifying the maximum rank indicator (βmax) is crucial as it signifies the optimal true target parameters. Rigorous validation is performed across two synthetic scenarios encompassing noisy, and multi-fault anomalies, affirming the approach's efficacy. Moreover, practical deployment on two distinct real datasets from geological hazards and hydrocarbon exploration endeavors in Egypt and USA underscores its effectiveness, versatility across diverse contexts, precision, and notable ability to operate sans prior knowledge of source shape, validated against borehole data and existing literature.