"Studying Fractures in Asmari Oil Reservoirs Using Image Logs for Better Understanding"

What is it about?

This study delves into characterizing fracture properties in naturally fractured reservoirs, which is a challenging task. Traditional well-testing methods often fall short in providing precise descriptions of these properties. To overcome this limitation, the study explores the use of Conventional Image Logs in analyzing the structural, fracture, and geomechanical aspects. However, effectively integrating these logs with well-test analysis on a broader scale reveals a significant knowledge gap. A key challenge is the absence of a clear procedure for calculating a critical parameter ("σ") necessary for simulating fractured carbonate reservoirs using image log fracture density. The integration of geological expertise is pivotal in reducing uncertainties associated with well-test analysis and providing more accurate characterizations of fracture properties. The study specifically focuses on characterizing fractures using data from ten image logs and improving simulation models by interpreting images, particularly emphasizing OBM imaging. The primary objectives include establishing correlations between fracture densities on a well-by-well basis within the simulation and refining the simulation model's accuracy by integrating fracture data from image logs. Tools like FMI/FMS and OBMI-UBI play a crucial role in identifying significant structural features such as faults, fractures, and bedding. Fine-tuning fracture parameters during the history matching process, although time-consuming, greatly influences the accuracy of reservoir simulation results, predictions, and strategies for enhancing recovery. Recent advancements in interpretation techniques have expanded possibilities for creating more accurate simulation models for fractured reservoirs using fracture data obtained from image logs. The ultimate aim of this project is to comprehensively evaluate a fractured reservoir field by amalgamating data from ten individual wells.

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Photo by Aleksei Zaitcev on Unsplash

Photo by Aleksei Zaitcev on Unsplash

Why is it important?

Understanding fracture properties in naturally fractured reservoirs is crucial for efficient resource extraction. Traditional well-testing methods often fall short in providing precise details about these properties, creating a significant challenge. This study aims to address this gap by utilizing Conventional Image Logs to delve into the structural, fracture, and geomechanical aspects of reservoirs. The integration of geological expertise with these logs is essential to enhance fracture assessment and reduce uncertainties associated with well-test analysis. By focusing on fracture characterization using data from ten image logs and refining simulation models through image interpretation, especially emphasizing OBM imaging, this study aims to establish correlations between fracture densities and improve the simulation model's accuracy. Identifying structural features like faults, fractures, and bedding using tools such as FMI/FMS and OBMI-UBI is pivotal. Accurately fine-tuning fracture parameters during the simulation process significantly impacts the reliability of reservoir simulation results, predictions, and strategies for enhancing recovery. Recent advancements in interpreting image logs have widened the scope for creating more precise simulation models using fracture data. Ultimately, this project's goal is to comprehensively evaluate a fractured reservoir field by integrating data from ten individual wells, which is essential for optimizing resource extraction and reservoir management strategies. This research is crucial for the oil and gas industry as it seeks to enhance understanding and improve the efficient extraction of resources from fractured reservoirs.

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