The objective of this study is to characterize fluid distributions in a presalt field by using well data including downhole fluid analysis (DFA) from wireline formation testers (WFT), openhole logs, and a simplified structural/geological model of the field. From an understanding of the petroleum system context of the field, reservoir fluid geodynamics (RFG) scenarios are developed to link the observations in the existing datasets and suggest opportunities to optimize the field development plan (FDP). DFA measurements of optical density (OD), fluorescence, inferred quantities of CO2 content, hydrocarbon composition, and gas/oil ratio of fluids sampled at discrete depth in six presalt wells are the basis of this study. DFA data at various depths captures fluid gradients for thermodynamic analysis of the reservoir fluids. OD linearly correlates with reservoir fluid asphaltene content. Gas-liquid equilibria are modeled with the Peng-Robinson equation of state (EOS) and solution-asphaltene equilibria with the Flory-Huggins-Zuo EOS based on the Yen-Mullins asphaltenes model. OD and other DFA measurements link the distribution of the gas, liquid, and solid fractions of hydrocarbon in the reservoir with reservoir architecture, hydrocarbon charging history, and postcharge RFG processes. Asphaltene gradient modeling with DFA reduces uncertainty in reservoir connectivity. The CO2 content in some sections of the field fluids limits the solubility of asphaltene in the oil, and the small asphaltene fraction exists in a molecular dispersion state according to the Yen-Mullins model. Low values of OD and small asphaltene gradients seen in most of the upper zones reflect the small asphaltenes concentration in the crude oil. The CO2 concentration was modeled with the modified Peng-Robinson EOS in good agreement with measurements in upper reservoir zones. Matching pressure regimes and asphaltene gradients in Wells B and C indicate lateral connectivity. The hydrocarbon column in this part of the reservoir is in thermodynamic equilibrium. In Wells A, C, D, E, and F the OD of the oil indicates an asphaltene content increase by a factor of four at the base of the reservoir as compared with the crest of the reservoir. This tripled the viscosity in Wells C and D, as indicated by in-situ viscosity measurements. The accumulation of asphaltenes at the bottom of the reservoir is most likely driven by a change in solubility resulting from thermogenic CO2 diffusion into the oil column from the top down. The challenge of the limited number of wells in the development phase of a presalt field for obtaining data to evaluate reservoir connectivity before the FDP is ably addressed by deploying the latest WFT technologies, including probes for efficient filtrate cleanup and fluid properties measurement. These measurements and methodology using a dissolved-asphaltene EOS enabled developing insightful RFG scenarios.
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.
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