Constrained LWD Resistivity Modeling for Improved Formation Evaluation of Horizontal Water Injectors
Abstract: TX 75083-3836, U.S.A., fax 01-972-952-9435.
Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Cited by 2 publications
References 7 publications
Accurate formation evaluation relies critically, among other inputs, on the correct true formation resistivity (Rt). The common practice in the industry is to use the deep resistivity log as Rt. A single resistivity curve from a deep resistivity measurement often does not represent Rt due to the shoulder bed effect, polarization at boundaries, and many other effects. This is especially true in high angle and horizontal wells. The main objective of the paper is to demonstrate that advanced resistivity modeling workflows for both wireline and logging while drilling (LWD) help in determining Rt by removing or minimizing the impact of all different effects and improving the formation evaluation in vertical and horizontal wells. Extensive work and computational advances have provided the oil and gas industry with codes to model resistivity tools in a wide variety of formations/conditions. The workflow used is a model-compare-update approach and provides an interface where a layered earth model (layer geometry and property) can be constructed. If available, image logs are used to provide dip information for each layer. After several iterations, and if an agreement between the forward model and measured logs has been achieved (called the "reconstruction check"), this will be a confirmation of the structural model and assigned layer properties. Reconstruction of actual data to modeled data is the confidence indicator. The model changes or iterations can be done manually or automatically. The practical process is usually a combination of both. As a result, the resistivity logs free of shoulder bed, polarization and other effects are extracted as squared logs for each layer and are used to improve the interpretation methodology and minimize the associated uncertainties to reservoir evaluation. The workflow and benefits of advanced resistivity modeling for improving formation evaluation in vertical and especially high angle and horizontal wells will be discussed. Several field log examples will be used to demonstrate the capabilities of the proposed workflow to enhance formation evaluation in vertical and horizontal wells. Conclusions fromthe work with suggestions/recommendations for the way forward will be presented. Advanced resistivity modeling when used by the petrophysicists can have many advantages, especially in complex situations. We propose workflows and case studies which demonstrate the value of such advanced modeling in enhancing vertical and horizontal well formation evaluation.
Accurate formation evaluation relies critically, among other inputs, on the correct true formation resistivity (Rt). The common practice in the industry is to use the deep resistivity log as Rt. A single resistivity curve from a deep resistivity measurement often does not represent Rt due to the shoulder bed effect, polarization at boundaries, and many other effects. This is especially true in high angle and horizontal wells. The main objective of the paper is to demonstrate that advanced resistivity modeling workflows for both wireline and logging while drilling (LWD) help in determining Rt by removing or minimizing the impact of all different effects and improving the formation evaluation in vertical and horizontal wells. Extensive work and computational advances have provided the oil and gas industry with codes to model resistivity tools in a wide variety of formations/conditions. The workflow used is a model-compare-update approach and provides an interface where a layered earth model (layer geometry and property) can be constructed. If available, image logs are used to provide dip information for each layer. After several iterations, and if an agreement between the forward model and measured logs has been achieved (called the "reconstruction check"), this will be a confirmation of the structural model and assigned layer properties. Reconstruction of actual data to modeled data is the confidence indicator. The model changes or iterations can be done manually or automatically. The practical process is usually a combination of both. As a result, the resistivity logs free of shoulder bed, polarization and other effects are extracted as squared logs for each layer and are used to improve the interpretation methodology and minimize the associated uncertainties to reservoir evaluation. The workflow and benefits of advanced resistivity modeling for improving formation evaluation in vertical and especially high angle and horizontal wells will be discussed. Several field log examples will be used to demonstrate the capabilities of the proposed workflow to enhance formation evaluation in vertical and horizontal wells. Conclusions fromthe work with suggestions/recommendations for the way forward will be presented. Advanced resistivity modeling when used by the petrophysicists can have many advantages, especially in complex situations. We propose workflows and case studies which demonstrate the value of such advanced modeling in enhancing vertical and horizontal well formation evaluation.
The main objective was to drill a power water horizontal injector within the sweet spot of a thin fractured and heterogeneous reservoir to achieve pressure stabilization in this producing field and an optimized sweep at the bottom of reservoir to maximize and prolong production. A traditional triple-combo logging while drilling (LWD) portfolio cannot fulfill these challenging reservoir navigation and formation evaluation (FE) objectives simultaneously because of the limited number of measurements. Hence, a more holistic approach is required to optimize the well placement via the integration of real-time LWD FE measurements to maximize the injectivity. An integrated LWD assembly was utilized and offset well FE data were studied to select the best zone for well placement to provide the best injectivity and production of the remaining oil towards the base of the reservoir. Extensive pre-well modeling was performed, based on offset well data with multiple scenarios reviewed to cover all eventualities. Another challenge was to place the wellbore in a relatively low resistive zone (water wet) in contrast to normal development wells where the wellbore is navigated in high resistive hydrocarbon bearing zones, so conventional distance to bed boundary mapping methodology was not applicable. To overcome this challenge; advanced Multi Component (MC) While Drilling resistivity inversion was proposed in conjunction with deep azimuthal resistivity technology. The benefit of this technique is in providing the resistivity of each layer within the depth of detection along with thickness and dip of each layer. Resistivity inversion results were correlated with nuclear magnetic resonance (NMR) porosity and volumetric data to identify the best zone for well placement. As MC inversion was able to map multiple layers within ~7 ft radius depth of detection, changing thicknesses and dip of each layer; the geosteering team was able to make proactive recommendations based on the inversion results. These proactive trajectory adjustments resulted in maintaining the wellbore within a thin target zone (1-3 ft in thickness) also confirmed by NMR and Formation Testing Service (FTS) in real-time, achieving excellent net-to-gross, which otherwise would not have been possible. The hexa-combo LWD assembly supported optimum well placement and provided valuable information about the geological structure through the analysis of high-resolution electrical images identifying the structural events which cause compartmentalization, confirmed by FTS results. This integrated LWD approach enabled proactive well trajectory adjustments to maintain the wellbore within the optimum porous, permeable and fractured target zone. This integrated methodology improved the contact within the water-injection target of the horizontal section, in a challenging thin reservoir and achieved 97.5 % exposure. Using an integrated LWD hexa-combo BHA and full real-time analysis the objective was achieved in one run with zero Non-Productive Time (NPT) and without any real-time or memory data quality issues.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
Contact Info
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Product
Resources
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.
