Processing Case Study with AVO and Pore Pressure Analyses: Eugene Island, Gulf of Mexico
type: CreativeWork
description: Seismic exploration uses numerous tools and techniques for detecting hydrocarbon reservoirs in conventional plays as found on the shelf of the northern Gulf of Mexico (GOM). The tools include seismic data-processing attributes, well-log calibration, and AVO (Amplitude Versus Offset) and pore pressure analyses. While the supporting theory for each method has been well established, an integration of the methods to a real exploration project can be confusing for the uninitiated. Given a seismic dataset and well-log curves, how exactly would someone process and analyze the data using the techniques listed? This research proposes a practical workflow for creating an end product for exploration applications. Using a seismic dataset in the GOM and several well log datasets, an integration of the processed seismic image with pore pressure analysis, petrophysical analysis and calibrated seismic attributes derived from the petrophysical analysis indicates the area would be classified as a Class III AVO environment which is supported by the geologic background. The dataset is further processed to completion and then used to generate AVO and pore pressure fields. Available well logs in the area are then compared and tied to the seismic, in order to validate the presence of any potential hydrocarbon attributes. An abnormal overpressure zone is determined by seismic velocity analysis and confirmed by the structural continuity of reflections, which was bound within a fault block. The seismic attributes indicated a potential gas reservoir on the downthrown side of the fault block, which would correlate with the proximity of the abnormal pressure. The exploration tools of seismic data analysis, well log analysis, AVO analysis, and pore pressure analysis are found to be strongly correlated by this study.
abstract: Seismic exploration uses numerous tools and techniques for detecting hydrocarbon reservoirs in conventional plays as found on the shelf of the northern Gulf of Mexico (GOM). The tools include seismic data-processing attributes, well-log calibration, and AVO (Amplitude Versus Offset) and pore pressure analyses. While the supporting theory for each method has been well established, an integration of the methods to a real exploration project can be confusing for the uninitiated. Given a seismic dataset and well-log curves, how exactly would someone process and analyze the data using the techniques listed? This research proposes a practical workflow for creating an end product for exploration applications. Using a seismic dataset in the GOM and several well log datasets, an integration of the processed seismic image with pore pressure analysis, petrophysical analysis and calibrated seismic attributes derived from the petrophysical analysis indicates the area would be classified as a Class III AVO environment which is supported by the geologic background. The dataset is further processed to completion and then used to generate AVO and pore pressure fields. Available well logs in the area are then compared and tied to the seismic, in order to validate the presence of any potential hydrocarbon attributes. An abnormal overpressure zone is determined by seismic velocity analysis and confirmed by the structural continuity of reflections, which was bound within a fault block. The seismic attributes indicated a potential gas reservoir on the downthrown side of the fault block, which would correlate with the proximity of the abnormal pressure. The exploration tools of seismic data analysis, well log analysis, AVO analysis, and pore pressure analysis are found to be strongly correlated by this study.
author: Kuo, Christine 1987-
language: eng
keywords: AVO pore pressure data processing Eugene Island Block 27 well tie log
date published: 2019-12
date modified: 2026-07-24T02:31:47Z
provider: University of Houston
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Houston

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10657/5557