What is it about?
The project focuses on using borehole imaging logs to detect faults and fractures within a reservoir. It aims to enhance reservoir modeling accuracy by incorporating fracture data from these logs. This study involves analyzing data from 10 wells to characterize fractures, correlate fracture densities across wells for simulation, and build a more precise simulation model using this fracture information. To create an accurate fractured reservoir model, detailed fracture network data is crucial. Utilizing the dual-porosity option in simulators, engineering parameters for two media and their flow patterns are prepared based on various data sources like well testing, core analysis, and geophysics. Information from well logs, especially fracture density, aperture, orientation, porosity, and permeability obtained through image logging, is essential for dual-porosity modeling. These data aid in estimating matrix block sizes, transmissibility, fracture properties, and aligning grid coordinates for optimal flow direction.
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Why is it important?
The project's significance lies in advancing borehole imaging techniques for reservoir analysis, particularly in characterizing fractures. These techniques have evolved, allowing for more precise interpretations and aiding in the creation of highly accurate simulation models for fractured reservoirs. This study aims to amalgamate data from ten wells to build a comprehensive model for assessing fractured reservoirs. It has three primary goals: characterizing fractures using data from ten image logs, correlating fracture densities across wells in simulations, and refining simulation models using fracture data from imaging logs. Accurate modeling of fractured reservoirs relies heavily on detailed fracture network information. This study leverages the dual-porosity option in conventional simulators, requiring detailed engineering parameters derived from various sources such as well testing, core analysis, logs, and geophysics. Well log data, especially fracture-related details like density, aperture, orientation, porosity, and permeability from image logs, significantly enhance dual-porosity modeling. These data enable better fluid flow modeling within the reservoir. For instance, fracture density aids in estimating matrix block size, which informs transmissibility between matrix and fracture (sigma). Aperture details help estimate fracture permeability and porosity, while fracture orientation assists in aligning grid coordinates for optimal flow direction. Ultimately, this approach enhances our ability to accurately model fluid flow in fractured reservoirs.
Perspectives
The ongoing advancements in interpreting borehole imaging logs have expanded our ability to uncover crucial details about a reservoir's structural features, especially faults and fractures. These developments now empower us to craft more precise simulation models for fractured reservoirs by harnessing fracture data from these imaging logs. This project endeavors to amalgamate data from ten individual wells to construct a comprehensive model for assessing a fractured reservoir field. This study is driven by three primary objectives: (1) characterizing fractures using information gleaned from 10 image logs, (2) establishing correlations between fracture densities across individual wells in simulation, and (3) enhancing simulation models by incorporating fracture data extracted from imaging logs. Accurately modeling fractured reservoirs necessitates intricate knowledge of the reservoir's fracture network. Achieving this requires employing the dual-porosity option available in conventional simulators. This technique involves preparing specific engineering parameters for both media and facilitating fluid flow through them. Data crucial for this modeling approach are acquired through various means such as well testing, core analysis, logs, and geophysics. Well log data significantly aids in fine-tuning fluid flow modeling within the media. Notably, fracture details including density, aperture, orientation, porosity, and permeability obtained from image logging data play a pivotal role in dual-porosity modeling. Fracture density, for instance, offers insights into matrix block size estimation in the model, thereby aiding in estimating sigma, which represents the transmissibility between matrix and fracture. Aperture information is crucial for estimating fracture permeability and porosity, while fracture orientation assists in aligning grid coordinates to optimize flow direction within the reservoir. Ultimately, this comprehensive approach enhances our ability to accurately model fluid flow in fractured reservoirs.
Dr Zohreh Movahed
zmovahed@gmail.com
Read the Original
This page is a summary of: A work flow for modeling the fractured reservoirs, January 2008, EAGE Publications,
DOI: 10.3997/2214-4609-pdb.246.256.
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