Integrated Hydrocarbon Detection Based on Full Frequency Pre-Stack Seismic Inversion

Abstract To improve the accuracy of hydrocarbon detection, seismic amplitude variation with offset (AVO), seismic amplitude variation with frequency (AVF), and direct hydrocarbon indicators (DHI) had been adopted in conventional methods. However, seismic amplitude responses are not straightforward with fluid properties but greatly affected by lithology and porosity. In this paper we present an integrated hydrocarbon detection method based on Full Frequency Seismic Inversion and pre-stack seismic inversion (Vp/Vs). The integrated hydrocarbon detection method mainly contains 5 steps. 1) Seismic data conditioning. Selecting sensitive frequencies to optimize the resolution of seismic data. 2) Rock physics analysis based on the rock type analysis. 3) Utilizing a new Full Frequency Seismic Inversion (FFI) method to improve the resolution and accuracy of seismic inversion. 4) Hydrocarbon detection based on the pre-stack inversion (Vp/Vs) based in the rock physical analysis. 5) Integration pre-stack inversion (Vp/Vs), well log interpretation, lithology and porosity from FFI for hydrocarbon detection QC and optimization to improve the accuracy of hydrocarbon detection results. This method was successfully applied in the K oil field. Comparative seismic data conditioning revealed that the sensitive frequency, enhancing seismic resolution. The Full Frequency Seismic Inversion (FFI) process involved 4 key components: a low-frequency model (<7 Hz) based on well logging data and controlled by seismic facies trends, conventional deterministic inversion (7-57 Hz) based on high-quality seismic data, mid- to high-frequency inversion (7-120 Hz) using seismic motion inversion, and high-frequency inversion (7-270 Hz) using geostatistical methods driven by well logs and seismic facies trends. The advantage of this method lies in its ability to integrate high-frequency well log information with seismic facies trends in areas without wells, obviously improving resolution and accuracy. The FFI method better predicts the lithology and porosity distribution. Pre-stack AVO and Vp/Vs inversions further enhanced hydrocarbon distribution predictions based on FFI results. Significant hydrocarbon response areas were identified by blind wells and new wells validation showing a 92% correlation between wells interpretations and hydrocarbon detection results. Well 07, drilled in the most promising area, achieved a production rate of 4,700 bbl/d, the highest oil production in the K oil field. The integrated hydrocarbon detection method has 3 main advantages. ① Seismic data conditioning can improve the quality of seismic data. ②Full Frequency Seismic Inversion (FFI) can improve the resolution and accuracy of seismic inversion, deepen geological understanding, and reduce the influence of lithology and porosity. ③The accuracy of hydrocarbon detection can be improved through multidisciplinary integrated analysis and QC. This method is applicable to clastic reservoirs and carbonate reservoirs.

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Published
2025-04-21
DOI
https://doi.org/10.2118/224658-ms
Primary Topic
Seismic Imaging and Inversion Techniques
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article
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Integrated Hydrocarbon Detection Based on Full Frequency Pre-Stack Seismic Inversion

Shize Wang, Xia Yaliang, Deng Xiao, Huang Kongzhi et al.
Seismic Imaging and Inversion Techniques
article

Integrated Hydrocarbon Detection Based on Full Frequency Pre-Stack Seismic Inversion

Shize Wang, Xia Yaliang, Deng Xiao, Huang Kongzhi, Wenyuan He, Xin Chen, Jiawen Song, Bo Wang, Yu Wenwen
article en

Abstract

Abstract To improve the accuracy of hydrocarbon detection, seismic amplitude variation with offset (AVO), seismic amplitude variation with frequency (AVF), and direct hydrocarbon indicators (DHI) had been adopted in conventional methods. However, seismic amplitude responses are not straightforward with fluid properties but greatly affected by lithology and porosity. In this paper we present an integrated hydrocarbon detection method based on Full Frequency Seismic Inversion and pre-stack seismic inversion (Vp/Vs). The integrated hydrocarbon detection method mainly contains 5 steps. 1) Seismic data conditioning. Selecting sensitive frequencies to optimize the resolution of seismic data. 2) Rock physics analysis based on the rock type analysis. 3) Utilizing a new Full Frequency Seismic Inversion (FFI) method to improve the resolution and accuracy of seismic inversion. 4) Hydrocarbon detection based on the pre-stack inversion (Vp/Vs) based in the rock physical analysis. 5) Integration pre-stack inversion (Vp/Vs), well log interpretation, lithology and porosity from FFI for hydrocarbon detection QC and optimization to improve the accuracy of hydrocarbon detection results. This method was successfully applied in the K oil field. Comparative seismic data conditioning revealed that the sensitive frequency, enhancing seismic resolution. The Full Frequency Seismic Inversion (FFI) process involved 4 key components: a low-frequency model (<7 Hz) based on well logging data and controlled by seismic facies trends, conventional deterministic inversion (7-57 Hz) based on high-quality seismic data, mid- to high-frequency inversion (7-120 Hz) using seismic motion inversion, and high-frequency inversion (7-270 Hz) using geostatistical methods driven by well logs and seismic facies trends. The advantage of this method lies in its ability to integrate high-frequency well log information with seismic facies trends in areas without wells, obviously improving resolution and accuracy. The FFI method better predicts the lithology and porosity distribution. Pre-stack AVO and Vp/Vs inversions further enhanced hydrocarbon distribution predictions based on FFI results. Significant hydrocarbon response areas were identified by blind wells and new wells validation showing a 92% correlation between wells interpretations and hydrocarbon detection results. Well 07, drilled in the most promising area, achieved a production rate of 4,700 bbl/d, the highest oil production in the K oil field. The integrated hydrocarbon detection method has 3 main advantages. ① Seismic data conditioning can improve the quality of seismic data. ②Full Frequency Seismic Inversion (FFI) can improve the resolution and accuracy of seismic inversion, deepen geological understanding, and reduce the influence of lithology and porosity. ③The accuracy of hydrocarbon detection can be improved through multidisciplinary integrated analysis and QC. This method is applicable to clastic reservoirs and carbonate reservoirs.

China National Petroleum Corporation (China) (CN)
Openalex Percentile: Top 89%
Seismic Imaging and Inversion Techniques
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