Well Productivity Prediction for Laminated Reservoirs Using Borehole Electrical Image Logs.

Chokthanyawat, Suchart; Daungkaew, Saifon; Athichanagorn, Suwat

doi:10.2523/iptc-14399-ms

Cited by 8 publications

(2 citation statements)

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“…In this complex geological setting, borehole imaging logs played a critical role in detecting the structural and reservoir geometry [3]. Accurate reservoir description through the use of image logs, particularly in thinly laminated reservoirs, emerged as a key factor in facilitating effective field development [4].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Fracture Density Distribution from Image Logs for Sensitivity Analysis in the Asmari Fractured Reservoir

Movahed,

Ashraf,

Movahed

2023

Earth Sciences and Human Constructions

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Characterizing fracture properties in naturally fractured reservoirs poses a significant challenge. While welltesting remains valuable, it often fails to provide precise descriptions of these properties. Bridging this gap requires the integration of geological expertise to enhance fracture assessment. This study addresses the limitations of well-test analysis and explores the application of Conventional Image Logs in structural, fracture, and geomechanical analysis. However, effectively combining these applications with well-test analysis on a field scale reveals a substantial knowledge gap. A critical challenge in this context is the absence of a defined procedure for calculating the variable "σ," a crucial parameter for simulating fractured carbonate reservoirs using image log fracture density. Integrating geological knowledge is essential to reduce uncertainties associated with well-test analysis and provide more accurate characterizations of fracture properties. Image log data processing emerges as a valuable avenue for gaining insights into the static attributes of naturally fractured reservoirs. This study focuses on Characterizing fractures using data from ten image logs and Developing a more accurate simulation model through the interpretation of images, with a particular emphasis on OBM imaging. The main goals of this fracture study revolve around establishing correlations between fracture densities well by well within the simulation and enhancing the accuracy of the simulation model by incorporating fracture data from image logs. Borehole imaging tools such as FMI/FMS and OBMI-UBI play a pivotal role in identifying significant structural features, including faults, fractures, and bedding. Fine-tuning fracture parameters during the history matching process, while potentially time-consuming, significantly impacts other historical match parameters. Consequently, the reliability of reservoir simulation results, predictions, and recovery enhancement strategies hinges on the precision of fracture properties and their distribution within the model. Recent advances in interpretation techniques have expanded the horizons of image interpretation, enabling the creation of more accurate simulation models for fractured reservoirs using fracture data obtained from image logs. The overarching goal of this project is to comprehensively evaluate a fractured reservoir field by integrating data from ten individual wells.

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Section: Introductionmentioning

confidence: 99%

Assessment of Fracture Density Distribution from Image Logs for Sensitivity Analysis in the Asmari Fractured Reservoir

Movahed,

Ashraf,

Movahed

2023

Earth Sciences and Human Constructions

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“…In this complex geological setting, borehole imaging logs (Chokthanyawat et al,2012) played a critical role in detecting the structural and reservoir geometry. Accurate reservoir description through the use of image logs, particularly in thinly laminated reservoirs, emerged as a key factor in facilitating effective field development (Yang, et al,2011).…”

Section: Introductionmentioning

confidence: 99%

Analytical Methods to Develop Accurate Structural Model for the Asmari Reservoir

Movahed,

Movahed

2023

International Journal of Chemical Engineering and Materials

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Crossing of Asmari can be a challenging endeavor in certain instances, particularly when dealing with structural complexities, compounded by the presence of a substantial layer of Gachsaran formation evaporates overlying the reservoir. The primary aim of this study was to establish a precise and comprehensive structural model for the Asmari reservoir. Utilizing geological logs for dip classification offers the advantage of directly depicting the structural origin. This approach helps in identifying the Asmari fault and fracture systems and their impact on production, ultimately resolving structural complexities. To investigate the reasons behind the intersection of the Kalhur member and the unexpected increase in the thickness of the Asmari formation, FMI data was acquired over the interval ranging from 1550m to 2065m. The analysis of picked bedding dips revealed abrupt variations in dip magnitude and azimuth reversals. These observations were pivotal in unraveling the structural intricacies of the reservoir. A significant fault was identified within zone five of the Kalhur member, and its interpretation suggests that it is a reverse fault. This conclusion is based on the observed dip pattern and the distinctive characteristics of the logs. Around the fault, the beds and layers exhibit elevated dips, largely attributed to the plastic nature of anhydrite and marly/shaly anhydrite within the formation. The anhydrite-indicator curve obtained from the FMI and gamma-ray logs provides further evidence that the well entered the Kalhur member after intersecting the major fault located within this particular zone. The interpretation of structural dip played a pivotal role in resolving structural complexities, leading to the precise determination of the well's location within the Asmari reservoir. This achievement was particularly critical as it enabled the well to reach the lower contact of the Asmari formation. This interpretation was facilitated by analyzing FMI images and petrophysical logs in well LL-26.

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Enhanced Reservoir Parameter Redistribution in Single Well Reservoir Modeling: An Inversion Approach Using Pressure Transient Analysis Data

Kumar,

Wydiabhakti,

Nukala

et al. 2024

SPE Western Regional Meeting

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Single Well Reservoir Modeling (SWRM) has been used mainly during the early exploration stage in order to perform productivity estimations and further, to optimize the completion strategy. However, its scope is limited due to the availability of petrophysical and dynamic pressure data from either single or few wells in the block. Variousmethods have been formulated in past to increase the robustness of SWRMs for relatively accurate forecasts. This research introduces a novel technique for the concurrent inversion of pivotal reservoirparameters – horizontal permeability, vertical permeability, skin, and boundary distances – for their spatialarrangement within the grid cells of a three-dimensional single well reservoir model (SWRM). The aim is to harnessthe interpretation results from standard pressure transient analysis of well test data, using it as a prioriinformation for the intricate inversion problem. Our methodology begins with crafting a layer cake geological model derived from the petrophysical analysis of logging data, calibrated by the interpretation results of well test pressure transient analysis. This is succeeded by a systematic flow simulation of field well test operations in the layer cake model, leading to the generation of model pressure data which mostly differs from the acquired well test pressure data. To ensure convergence, we define a cost function that amalgamates both the well test pressure data and the model pressure data. This cost function depends on the reservoir parameters like horizontal permeability, vertical permeability, skin and boundary distances, which need to be refined to achieve a pressure history match. To do that we introduce an inversion approach, where simultaneous inversion of all these reservoir parameters take place in an iterative manner to minimize the cost function. Crucially, our inversion methodology is tightly regulated by a multiphase fluid flow simulator, which constantly solves the implicit black-oil fluid-flow diffusivity equations at each iteration to calculate the error between model pressure and acquired well test pressure. A range including minima and maxima of each property is provided to the inversion scheme, which ensures that at each iteration, we gain a renewed distribution of reservoir parameters. These parameters, in turn, feed into an error scheme steered by the cost function. A Gauss-Newton (GN) inversion method, complemented by a regularization technique, facilitates inversion-based re-distribution of properties across geomodel grid cells. To enhance the fidelity of inversion outcomes, the a priori parameters provided to the solver are rigorously assessed, and if needed, fine-tuned via uncertainty parameter optimization (UPO). The proposed technique offers a swifter and more dependable method forredistributing reservoir parameters in a homogenous layer cake geomodel, infusing it with the much-neededheterogeneity. Such methodical redistribution not only augments the reliability and credibility of a geomodel butalso sets it up as a robust foundation for production forecasting strategies.

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Well Productivity Prediction for Laminated Reservoirs Using Borehole Electrical Image Logs.

Cited by 8 publications

References 0 publications

Assessment of Fracture Density Distribution from Image Logs for Sensitivity Analysis in the Asmari Fractured Reservoir

Assessment of Fracture Density Distribution from Image Logs for Sensitivity Analysis in the Asmari Fractured Reservoir

Analytical Methods to Develop Accurate Structural Model for the Asmari Reservoir

Enhanced Reservoir Parameter Redistribution in Single Well Reservoir Modeling: An Inversion Approach Using Pressure Transient Analysis Data

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