Shear wave velocity prediction: A review of recent progress and future opportunities

Abstract

Shear logs, also known as shear velocity logs, are used for various types of seismic analysis, such as determining the relationship between amplitude variation with offset (AVO) and interpreting multiple types of seismic data. This log is an important tool for analyzing the properties of rocks and interpreting seismic data to identify potential areas of oil and gas reserves. However, these logs are often not collected due to cost constraints or poor borehole conditions possibly leading to poor data quality, though there are various approaches in practice for estimating shear wave velocity. In this study, a detailed review of the recent advances in the various techniques used to measure shear wave (S-wave) velocity is carried out. These techniques include direct and indirect measurement, determination of empirical relationships between S-wave velocity and other parameters, machine learning, and rock physics models. Therefore, this study creates a collection of employed techniques, enhancing the existing knowledge of this significant topic and offering a progressive approach for practical implementation in the field.

Keywords

• Shear wave (S-wave) velocity
• Direct and indirect measurement
• Empirical relationship
• Artificial intelligence (AI)
• Machine learning
• Rock physics model