A Procedure to Parameterize High Permeability Zones in Naturally Fractured Reservoir

This paper presents a novel-methodology to compensate for the poor characterization of high-permeability structures (excess-K: vugs, karsts and super-K features), and non-fault-related-fractures, in naturally fractured Brazilian Pre-Salt carbonate reservoirs. These heterogeneities are often undetectable in well logs and seismic data, but significantly impact well performance. The methodology aims to enhance the representation of such features within dynamic simulation models, improving reservoir characterization and supporting more reliable data-assimilation and forecasting processes. The methodology involves: (1) upscaling high-fidelity fine-grid models to coarser-grids while preserving dynamic behavior, (2) identifying wells with productivity/injectivity mismatches due to a poor excess-K characterization, (3) applying a data assimilation (DA) process to minimize the mismatch between modeled and measured wells production and injection rates by updating the absolute permeability of the matrix. The novelty of the process is that the permeability field is updated by creating a mask (3D property) built by kriging permeability increments estimated from the well cells with productivity/injectivity issues. Therefore, the DA aims to find the least increments of permeability needed for each well such that when this mask is summed with the matrix permeability field all wells present good productivity/injectivity matching with history data. The methodology was applied to a dual-porosity/dual-permeability (DP/DK) compositional reservoir model. Two distinct well behaviors were observed: (1) wells located within fracture zone (12 of 33) showed good productivity/injectivity alignment with historical data and (2) the remaining 21 wells, located away from fracture zone, exhibited significantly poorer productivity/injectivity. This mismatch was attributed to the absence of excess-K features in the original matrix permeability model (Km-field). The optimization process was applied to these 21 wells. For each well a specific Ki-value was settled, defining input-points for kriging. The resulting kriged permeability correction volume (mask) was summed with the Km-field to generate an updated-permeability model. This process was repeated until all wells presented good productivity/injectivity matching with historical data. The process not only corrected the simulated dynamic responses, but also revealed key spatial permeability patterns that had not been captured in the static model. The results served as feedback to the geologists and enabled iterative improvement of the geological model, supporting a more integrated and realistic characterization. Overall, the results validate the methodology as a robust tool for incorporating unresolved high-permeability features in reservoir simulation and improving the quality of data assimilation. This study introduces an automated, iterative probabilistic data-assimilation framework that directly integrates geostatistical kriging with permeability adjustments for excess-Kstructures. The approach provides bidirectional feedback to geological modeling and allows the generation of realistic ensembles for data assimilation workflows. By combining geo-statistics within an uncertainty reduction scheme, the method addresses key modeling gaps encountered when modelling a Brazilian Pre-Salt carbonate.

Fast Objective Function Estimator Based on Parametric Dynamic Mode Decomposition for Wag-Co2 Injection in Carbonate Reservoirs

Objective/Scope

Fast-objective function estimators (FOFE) are often used to speed up reservoir management. This work presents a FOFE constructed with the parametric Dynamic Mode Decomposition (DMDp) method for a carbonate reservoir with WAG-CO2 injection. The FOFE results are then compared to simulation results to analyze the FOFE’s efficiency.

Method/Procedure/Process

We present an example of how changes in the production strategy can affect reservoir behavior. The FOFE utilizes snapshots of gas and water saturation of numerical simulation runs with different sizes of WAG-CO2 cycles to predict the snapshots and fluid rates of a production strategy with a desired WAG-CO2 cycle size. The FOFE utilizes the DMDp method to calculate the saturation snapshots and material balance equations to calculate oil, water, and gas rates. Unlike the standard where snapshots are stacked up for multiple parameters, leading to increased computational costs, here we perform interpolation directly on the reduced Koopman operator. This leads to enhanced performance as the time eigenvalues are no longer shared between all parameters. The case study is the public access benchmark UNΊSFM-ΓV-2022, a carbonate reservoir model with characteristics of the Brazilian pre-salt. This model represents a developed reservoir with a WAG-CO2 recovery method for a compositional simulator with historical data.

Results/Observations/Conclusions

For this work, the FOFE utilizes snapshots of two reservoir simulations, one with a WAG-CO2 cycle size of 6 months and the other with 18 months, to predict the states of a production strategy with 12 months of WAG-CO2 cycle. The FOFE results of gas, oil, and water are compared to a simulation result with the same production strategy. The comparisons for fluid dynamics are shown for reservoir conditions, and their curves with relative differences are provided. The FOFE can predict the states of a different field scenario, dispensing the necessity of extra numerical simulation runs. This result is promising for production optimization problems which require a significant amount of simulation runs to incorporate the many reservoir uncertainties, as it is observed in highly heterogeneous carbonate reservoirs.

Novel/Additive Information

The innovation of this work is the utilization of the DMDp in a highly heterogeneous reservoir with three-phase flow and WAG-CO2 injection utilizing commercial software. This FOFE can be utilized to reduce the time and computational effort necessary for the decision-making process involving the control variable of WAG-CO2 cycle size.

Numerical Study on the Impact of Advanced Phenomena in a Fractured Carbonate Reservoir Subjected to WAG-CO2 Injection

Advanced phenomena related to water-alternating-gas (WAG) injection are usually neglected in numerical simulations. This work evaluates the impact of different physical phenomena on field indicators, considering a typical pre-salt carbonate reservoir (UNISIM-II-D-CO, a dual-por dual-perm compositional case) subjected to WAG-CO2 injection. Additionally, the computational cost incurred by each of these phenomena is evaluated, since it represents a great challenge in optimization and probabilistic studies. The following phenomena are evaluated considering a nominal base case: (i) matrix-fracture transfer calculation, (ii) relative permeability hysteresis, (iii) CO2 and CH4 solubilities in aqueous phase, (iv) diffusion, (v) numerical dispersion control models, and (vi) velocity-dependent dispersion. CO2 and CH4 solubilities in the aqueous phase, as well as molecular diffusion, did not have a significant impact on field indicators, but they increased simulation runtime more than two times. Matrix-fracture transfer modeling was the most impactful factor, followed by hysteresis and velocity-dependent dispersion. Therefore, the impact of these phenomena was also investigated in a probabilistic approach, considering an ensemble of 197 geostatistical scenarios under uncertainty. Risk curves revealed that the advanced matrix-fracture transfer models improve sweep efficiency. This effect is mainly due to gravity force which acts as a driving mechanism for the oil moving from the matrix to fractures. The capillary effect, in turn, was small compared to gravity. The impact of dispersion and hysteresis on risk curves were smaller than the effect of matrix-fracture transfer modelling. However, these phenomena are particularly interesting in UNISIM-II-D-CO due to the presence of Super-K facies. Hysteresis, when applied to low and high permeability layers, reduced gas mobility and, consequently, the gas produced, contributing to the NPV for most models under uncertainty. On the other hand, the velocity-dependent dispersion mainly affected fluid flows in the regions adjacent to Super-K layers, promoting better oil recovery. The inclusion of advanced phenomena related to WAG-CO2 injection can hold importance when modeling fractured carbonate fields, like those found in the Pre-Salt in Brazil. Nevertheless, computational costs might make their inclusion impractical in full-field simulation models employed for optimization and probabilistic studies. In such cases, it is recommended to assess low-fidelity models or alternatives to accelerate simulations, focusing mainly on the most impactful phenomena related to WAG-CO2 injection.

Understanding ESP Performance Under High Viscous Application and Emulsion Production

Although being widely used as an artificial lift method for heavy oil field developments, Electrical Submersible Pump (ESP) system performance in high viscous applications is not fully understood. A miscomprehension of challenges and equipment performance in such conditions might lead to operation inefficiencies and equipment failures. This paper presents results of single-phase and multiphase tests performed by University of Campinas (UNICAMP). It also presents operation data, lessons learnt, and failure examples gathered over 10 years of ESP operation in Peregrino field which is a heavy oil, high viscous oilfield offshore Brazil operated by Equinor.

Affinity laws commonly used for ESP simulations don’t hold true for high viscosity applications. Hydraulic performance of centrifugal pumps is affected by fluid parameters like viscosity and density; operation parameters such as flow rate and rotational speed; and specific stage design characteristics. To determine degradation in head and efficiency as well as power requirement increase in viscous applications, Equinor performs one-phase high viscosity flow loop test to qualify each stage type prior to deployment in Peregrino field.

For the qualification of ESPs, single phase qualification tests are performed using mineral oil with viscosities specifically chosen to cover the viscosity range of the specific field. Each stage type is qualified using a prototype with reduced number of stages due to flow loop limitations. Qualification tests for the Peregrino field confirmed that affinity laws are not accurate for high viscous applications and provided important insights regarding pump performance that are used in equipment specification and system surveillance.

The UNICAMP research team has designed and performed multiphase flow tests to evaluate emulsion formation inside centrifugal pump stages and effective viscosity behavior. Phase inversion phenomenon investigation was also included in studies. Studies performed using a prototype stage allowed visualization and evaluation of oil drops dynamics inside the impeller in different rotational speeds. Two phase flow loop tests investigated the shear forces influence in effective viscosity inside pump stages and downstream pump discharge. Phase inversion phenomenon was also a point of great interest during the studies. Data gathered during lab tests was used to evaluate accuracy of mathematical models existing in the literature when a centrifugal pump is added to the system. Hysteresis effect associated to catastrophic phase inversion (CPI) was confirmed and replicated during flow loop tests. Such behavior can be related with operation parameters instabilities and equipment failures noticed in actual application in Peregrino field which are also presented in this paper.

Construction of Single-Porosity and Single-Permeability Models as Low-Fidelity Alternative to Represent Fractured Carbonate Reservoirs Subject to WAG-CO2 Injection Under Uncertainty

Fractured carbonate reservoirs are typically modeled in a system of dual-porosity and dual-permeability (DP/DP), where fractures, vugs, karsts and rock matrix are represented in different domains. The DP/DP modeling allows for a more accurate reservoir description but implies a higher computational cost than
the single-porosity and single-permeability (SP/SP) approach. The time may be a limitation for cases that require many simulations, such as production optimization under uncertainty. This computational cost is more challenging when we couple DPDP models with compositional fluid models, such as in the case of fractured light-oil reservoirs where the production strategy accounts for water-alternating-gas (WAG) injection. In this context, low fidelity models (LFM) can be an interesting alternative for initial studies. This work shows the potential of compositional single-porosity and single-permeability models based on pseudo-properties (SP/SP-P) as LFM applied to a fractured benchmark carbonate reservoir, subject to WAG- CO2 injection and gas recycle. Two workflows are proposed to assist the construction of SP-P models for studies based on (i) nominal approach and (ii) probabilistic approach of reservoir properties. Both workflows begin with a parametrization step, in which the pseudo-properties are optimized for a base case in order to minimize the mismatch between forecasts of the SP/SP-P and DP/DP models. The new parametrization methods proposed in this work showed to be viable for the construction of the SP/SP-P models. For studies under uncertainties, the workflow proposes obtaining pseudo-properties by robust optimizations based on representative models from a DP/DP ensemble, which proved to be an effective method. The case study is the benchmark UNISIM-II-D-CO with an ensemble of 197 DP/DP models and two different production strategies. The risk curves for production, injection and economic indicators obtained from DP/DP and SP/SP-P ensembles showed good match and the computational time spent on simulations of the SP/SP-P ensemble was 81% faster than DP/DP models, on average. Finally, the responses obtained from both ensembles were validated in a reference model (UNISIM-II-R) that represents the true response and is not part of the ensemble. The results indicate the SP/SP-P modeling as a good LFM for preliminary assessments of highly time-consuming studies. Besides, the workflows proposed in this work can be very useful for assisting the construction of SP/SP-P models for different case studies. However, we recommend the use of the high-fidelity models to support the final decision.