Tag: Artificial intelligence
Experimental Investigation of Polymer Degradation and Its Effects on Electrical Submersible Pump Operation
Model-Based Petroleum Field Management in Three Stages: Life-Cycle, Short-Term, and Real-Time
The objective of this work is to present a new practical methodology to manage petroleum fields considering three stages (life-cycle, short-term, and real-time) that can run alongside different model fidelities and characteristics. The model-based field management process follows the general methodology proposed by Schiozer et al. (2019) with four activities: (1) fit-for-purpose models construction, (2) data assimilation for uncertainty reduction, (3) life-cycle production optimization and (4) short-term optimization for real-time implementation. The selection of the production strategy for field management comprehends the last two activities. Life-cycle optimization is the first stage of the process and generates control setpoints for short-term analysis. Short-term optimization is then used to improve the quality of the solutions considering the control parameters of the next cycle (considering a closed-loop procedure). Real-time solution is then implemented considering operational disturbances from real operations. The methodology was applied to a benchmark case (UNISIM-IV-2026) which is a case based on a typical carbonate field from the Brazilian Pre-salt, with light oil and submitted to Water-Alternate-Gas injection with CO2 (WAG-CO2). The results show that the methodology is applicable to real and complex fields. As the three stages can run simultaneously, one can (1) use different model fidelities to improve the quality of the solutions and (2) use model-based solutions for real-time implementation. Life-cycle optimization using complex simulation models and long-term objectives can run in the background to generate control setpoints for short-term analysis in which lower fidelity models and simplified solutions can be used for the control and field revitalization parameters of each closed-loop cycle. Real-time solutions can be implemented considering operational problems and disturbances. This work presents a novel procedure to integrate three stages for production optimization that can run in parallel, allowing the integration of life-cycle and real-time solutions. The methodology (1) allows the use of complex reservoir simulation models from the life-cycle production strategy optimization, (2) focuses short-term control parameters that improve the quality of the short-term solution, and (3) guides real-time implementation, so it can be the basis to a digital field management.
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.
Comparing WAG-CO 2 injection with continuous water and gas injection in separate wells for the development and management of a CO2-rich light oil fractured carbonate reservoir subject to full gas recycling
Many projects in the Brazilian pre-salt assume the use of water alternating gas (WAG-CO2) injection as an ecologically safe carbon storage strategy, with improved hydrocarbon recovery. However, studies that compare these advantages with a simpler management plan are not common. The objective of this work is to compare WAG-CO2 injection with continuous injection of water and gas (CIWG) rich in CO2 in separate wells for the development and management of a light-oil fractured carbonate reservoir subject to full gas recycling. We employed the UNISIM-II benchmark model, a naturally fractured carbonate reservoir with Brazilian pre-salt characteristics, which enables an application in controlled environment where the reference response is known (UNISIM-II-R). We used a model-based decision analysis for production strategy selection, hierarchical optimization of the decision variables and algorithms to maximize the objective function. Representative models (RM) are selected from the ensemble of models and used to incorporate the effects of geological, reservoir, and operational uncertainties into the optimization process. The net present value is the objective function during the nominal optimization of candidate strategies of each RM and the expected monetary value and risk analysis are considered to select the final production strategy considering uncertainties. The risk analysis was quantified based on downside risk and upside potential relation to a benchmark return. We optimized two alternative development plans (one considering WAG-CO2 injection and the other continuous injection of water and gas in separate wells) and compared their performance indicators and decision variables, including design variables (number, type and placement of well, and size of production facilities) and life-cycle control rules (management of equipment over time). We then applied a cross-simulation, where the best strategy optimized for one recovery method was applied to the other and the injection strategy was optimized again. We were therefore able to assess the need to pre-define the recovery method before defining design variables to validate the flexibility of each strategy for possible future changes in the recovery mechanism. Finally, we repeated the study for different reservoir scenarios to compare the alternatives considering typical uncertainties of the Brazilian pre-salt and validated the final strategies in the reference model to quantify the real value in decision making. The strategies reached a full gas recycling in both recovery methods and allowed a comparison of their advantages and disadvantages. The operations of WAG-CO2 injection can be more complex and the equipment more expensive. The novelty of this work is the consideration of continuous injection of water and gas in separate wells as a simpler alternative to the development and management of pre-salt oil fields, since this method may also meet operators’ and environmental demands, bearing simpler operating challenges and promoting good recovery and profitability.
Model-Based Life-Cycle Optimization for Field Development and Management Integrated with Production Facilities
Reservoir simulation models often support decision making in the development and management of petroleum fields. The process is complex, sometimes treated subjectively, and many methods and parameterization techniques are available. When added to uncertainties, the lack of standardized procedures may yield largely suboptimal decisions. In this work, we present a comprehensive outline for model-based life-cycle production optimization problems, establishing guidelines to make the process less subjective. Based on several applications and a literature review, we established a consistent methodology by defining seven elements of the process: (1) the degree of fidelity of reservoir models; (2) objective function (single- or multi-objective, nominal or probabilistic); (3) integration between reservoir and production facilities (boundary conditions, IPM); (4) parametrization (design, control and revitalization optimization variables); (5) monitoring variables (for search space reduction); (6) optimization method, including optimizer/ algorithm, search space exploration, faster-objective function estimators (coarse models, emulators, others), type of ensemble-based optimization (robust or nominal based on representative models); (7) additional improvements (value of information and flexibility). With an application on a publicly available benchmark reservoir, this work shows how a model-based life-cycle optimization process can be systematically defined. In this initial work, the focus is the field development phase and some simplifications were made due to the high computational demand, but in future works we plan to address the control and revitalization variables and reduce the number of simplifications to compare. The optimization results are analyzed to understand the evolution of the objective function and the evolution of the optimization variables. We also discuss the importance of including uncertainties in the process and we discuss future work to emphasize the difference between life-cycle (control rules) and short-term (effective control) management of equipment, as well as ways to deal with the computational intensity of the problem, such as the combined use of representative models and fast simulation models.
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.
Selection of Representative Scenarios Using Multiple Simulation Outputs for Robust Well Placement Optimization in Greenfields
In greenfield projects, robust well placement optimization under different scenarios of uncertainty technically requires hundreds to thousands of evaluations to be processed by a flow simulator. However, the simulation process for so many evaluations can be computationally expensive. Hence, simulation runs are generally applied over a small subset of scenarios called representative scenarios (RS) approximately showing the statistical features of the full ensemble. In this work, we evaluated two workflows for robust well placement optimization using the selection of (1) representative geostatistical realizations (RGR) under geological uncertainties (Workflow A), and (2) representative (simulation) models (RM) under the combination of geological and reservoir (dynamic) uncertainties (Workflow B). In both workflows, an existing RS selection technique was used by measuring the mismatches between the cumulative distribution
of multiple simulation outputs from the subset and the full ensemble. We applied the Iterative Discretized Latin Hypercube (IDLHC) to optimize the well placements using the RS sets selected from each workflow and maximizing the expected monetary value (EMV) as the objective function. We evaluated the workflows in terms of (1) representativeness of the RS in different production strategies, (2) quality of the defined robust strategies, and (3) computational costs. To obtain and validate the results, we employed the synthetic UNISIM-II-D-BO benchmark case with uncertain variables and the reference fine- grid model, UNISIM-II-R, which works as a real case. This work investigated the overall impacts of the robust well placement optimization workflows considering uncertain scenarios and application on the reference model. Additionally, we highlighted and evaluated the importance of geological and dynamic uncertainties in the RS selection for efficient robust well placement optimization.