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Izadi, Mohammad (Louisiana State University) | Nguyen, Phuc H. (Louisiana State University) | Fleifel, Hazem (Louisiana State University) | Maestre, Doris Ortiz (Ecopetrol) | Kam, Seung I. (Louisiana State University)
Summary While there are a number of mechanistic foam models available in the literature, it still is not clear how such models can be used to guide actual field development planning in enhanced oil recovery (EOR) applications. This study aims to develop the framework to determine the optimum injection condition during foam EOR processes by using a mechanistic foam model. The end product of this study is presented in a graphical manner, based on the sweep-efficiency contours (from reservoir simulations) and the reduction in gas mobility (from mechanistic modeling of foams with bubble population balance). The main outcome of this study can be summarized as follows: First, compared to gas/water injection with no foams, injection of foams can improve cumulative oil recovery and sweep efficiency significantly. Such a tendency is observed consistently in a range of total injection rates tested (low, intermediate, and high total injection rates Qt). Second, the sweep efficiency is more sensitive to the injection foam quality fg for dry foams, compared to wet foams. This proves how important bubble-population-balance modeling is to predict gas mobility reduction as a function of Qt and fg. Third, the graphical approach demonstrates how to determine the optimum injection condition and how such an optimum condition changes at different field operating conditions and limitations (i.e., communication through shale layers, limited carbon dioxide (CO2) supply, cost advantage of CO2 compared to surfactant chemicals, etc.). For example, the scenario with noncommunicating shale layers predicts the maximum sweep of 49% at fg = 55% at high Qt, while the scenarios with communicating shale layers (with 0.1-md permeability) predicts the maximum sweep of only 40% at fg = 70% at the same Qt. The use of this graphical method for economic and business decisions is also shown, as an example, to prove the versatility and robustness of this new technique.
Abstract Accurate oil production monitoring is essential for scheduling well work and optimizing the economic performance of primary and enhanced recovery projects. The significance of water cut monitoring accuracy on oil rate determination is discussed and illustrated. This paper provides a comprehensive uncertainty analysis of several water cut monitoring methods commonly employed by oil field operators. These include liquid sampling, capacitance, microwave, ultrasonic, spectroscopy and density methods. The basic operating principles of each monitoring method are described and measurement uncertainty analysis procedures are employed to identify key parameters that affect the overall accuracy of each water cut monitoring method. The analysis results provide useful accuracy assessments that can be used in water cut meter selection, field testing and implementation.
Abstract Controlling excessive water production in mature oil fields has always been one major objective of the oil and gas industry. This objective calls for planning of more effective water-control treatments with optimized designs to obtain more attractive outcomes. Unfortunately, planning such treatments still represents a dilemma for conformance experts due to the lack of systematic design tools in the industry. This paper proposes and makes available a new design approach for bulk gel treatments by grouping designs of 62 worldwide field projects (1985-2018) according to gel volume-concentration ratio (VCR). After compiling them from SPE papers, the average gel volumes and polymer concentrations in the field projects were used to evaluate the gel VCR. Distributions of field projects were examined according to the gel VCR and the formation type using stacked histograms. A comprehensive investigation was performed to indicate the grouping criterion and design types of gel treatments. Based on mean-per-group strategy, the average VCR was estimated for each channeling and formation type to build a three-parameter design approach. Two approximations for the average polymer concentration and two correlations for minimum and maximum designs and were identified and included in the approach. The study shows that the gel VCR is a superior design criterion for in-situ bulk gel treatments. Field applications tend to aggregate in three project groups of clear separating VCR cut-offs (<1, 1-3, >3 bbl/ppm). The channeling type is the dividing or distributing criterion of the gel projects among the three project groups. We identified that VCRs<1 bbl/ppm are used to treat conformance problems that exhibit pipe-like channeling usually presented in unconsolidated and fractured formations with very long injection time (design type I). For fracture-channeling problems frequently presented in naturally or hydraulically-fractured formations, VCRs of 1-3 bbl/ppm are used (design type II). Large gel treatments with VCR>3 bbl/ppm are performed to address matrix-channeling often shown in matrix-rock formations and fracture networks (design type III). Results show that the VCR approach reasonably predicts the gel volume and the polymer concentration in training (R of 0.93 and 0.67) and validation (AAPE <22%) samples. Besides its novelty, the new approach is systematic, practical, and accurate, and will facilitate the optimization of the gel treatments to improve their performances and success rate.
Abstract This study designs a novel complex fluid (foam/emulsion) using as main components gas, low-toxicity solvents (green solvents) which may promote oil mobilization, and synergistic foam stabilizers (i.e. nanoparticles and surfactants) to improve sweep efficiency. This nanoparticle-enabled green solvent foam (NGS-foam) avoids major greenhouse gas emissions from the thermal recovery process and improves the performance of conventional green solvent-based methods (non-thermal) by increasing the sweep efficiency, utilizing less solvent while producing more oil. Surfactants and nanoparticles were screened in static tests to generate foam in the presence of a water-soluble/oil-soluble solvent and heavy crude oil from a Canadian oil field (1600 cp). The liquid phase of NGS-foam contains surfactant, nanoparticle, and green solvent (GS) all dispersed in the water phase. Nitrogen was used as the gas phase. Fluid flow experiments in porous media with heterogeneous permeability structure mimicking natural environments were performed to demonstrate the dynamic stability of the NGS-foam for heavy oil recovery. The propagation of the pre-generated foam was monitored at 10 cm intervals over the length of porous media (40 cm). Apparent viscosity, pressure gradient, inline measurement of effluent density, and oil recovery were recorded/calculated to evaluate the NGS-foam performance. The outcomes of static experiments revealed that surfactant alone cannot stabilize the green solvent foam and the presence of carefully chosen nanoparticles is crucial to have stable foam in the presence of heavy oil. The results of NGS-foam flow in heterogeneous porous media demonstrated a step-change improvement in oil production such that more than 60% of residual heavy oil was recovered after initial waterflood. This value of residual oil recovery was significantly higher than other scenarios tested in this study (i.e. GS- water and gas co-injection, conventional foam without GS, GS-foam stabilized with surfactant only and GS-waterflood). The increased production occurred because NGS-foam remained stable in the flowing condition, improves the sweep efficiency and increases the contact area of the solvent with oil. The latter factor is significant: comparing to GS-waterflood, NGS-foam produces a unit volume of oil faster with less solvent and up to 80% less water. Consequently, the cost of solvent per barrel of incremental oil will be lower than for previously described solvent applications. In addition, due to its water solubility, the solvent can be readily recovered from the reservoir by post flush of water and thus re-used. The NGS-foam has several potential applications: recovery from post-CHOPS reservoirs (controlling mobility in wormholes and improving the sweep efficiency while reducing oil viscosity), fracturing fluid (high apparent viscosity to carry proppant and solvent to promote hydrocarbon recovery from matrix while minimizing water invasion), and thermal oil recovery (hot NGS-foam for efficient oil viscosity reduction and sweep efficiency improvement).
Summary In recent years, the advancement of horizontal-well technology has played a major role in making oil production economically feasible from many reservoirs. One of the major problems that can reduce the efficiency of using horizontal wells is gas and water coning caused by the heel-toe effect and heterogeneity along the well. To tackle this problem, Equinor’s autonomous inflow-control device (ICD) (AICD), known as rate-controlled production (RCP) valves, is widely used today. RCP valves can effectively delay the early water breakthrough and partially choke back water autonomously after water breakthrough. To fulfill a suitable design of a long horizontal well with the RCP completion, a detailed understanding of multiphase-flow behavior from the reservoir pore to the wellbore and production tubing is needed. Coupling a dynamic multiphase-flow simulator such as the OLGA (Schlumberger Limited, Sugar Land, Texas, USA) simulator with the near-wellbore reservoir module such as the OLGA ROCX module provides a robust tool for achieving this purpose. However, there is no predefined option in the OLGA simulator for implementing the autonomous behavior of the RCP valves directly. Therefore, creating a model of oil production by considering well completion with the RCP valves in the OLGA simulator is challenging. In the previous works, this has been performed by using the Proportional Integral Derivative (PID) Controller option in the OLGA simulator, which controls the opening of an equivalent orifice valve according to the fixed value of the water cut. However, because of the performance of the PID Controller using a fixed setpoint and the difficulties in properly tuning the PID Controller, choosing this option leads to a large degree of inaccuracy in the simulation models. In this paper, by proposing a novel method with a developed mathematical model and a control function for the RCP valves, the autonomous behavior of these valves is implemented in the OLGA simulator. In this new approach, the control signals are calculated using the variation of water cut and introduced to the OLGA simulator through the Table Controller option instead of the PID Controller. The presented approach in this paper can be used for the simulation of water-cut (or gas/oil-ratio) reduction potential of all RCP-type AICDs in reservoirs with different characteristics. However, to explain the procedure of this approach in detail, the near-well oil production from Well 16/2-D-12 in the Johan Sverdrup Field (JSF) considering RCP completion is modeled as a case study. In this study, the simulation model is developed using one of the commonly used types of RCP valves called the TR7 RCP valve. Version 2016.1.1 of the OLGA simulator/ROCX module is used (Schlumberger 2016). According to the simulation results, compared with using ICDs, by the completion of Well 16/2-D-12 with RCPs, the water cut, water-flow rate, and accumulated water production can be reduced by 2.9, 13.3, and 12.1%, respectively, after 750 days. The results also showed that by using the proposed approach, the autonomous behavior of the RCP valves according to the water-cut variations can be appropriately implemented in the OLGA simulator. This can help engineers and researchers to achieve a better design of a long horizontal well using the RCP completion. Consequently, using this approach can be beneficial for improving technology, optimizing production, minimizing risk, and reducing costs in oil recovery.
The water-shutoff technique is used in some wells of the U reservoir in the Iro field of the Oriente Basin in Ecuador as a remediation plan to restore production after an early water breakthrough. The production historical data, workovers, and sand-body correlation of wells are compared to understand reservoir behavior, shale-baffle-sealing continuity, the existence of different sand units, and the effect on production. The Iro field is in the south of Block 16. Production began in March of 1996. Iro is considered a mature field that produces heavy crude oil.
Ma, Kuiqian (Tianjin Branch of CNOOC (China) Co., Ltd) | Chen, Cunliang (Tianjin Branch of CNOOC (China) Co., Ltd) | Zhang, Wei (Tianjin Branch of CNOOC (China) Co., Ltd) | Liu, Bin (Tianjin Branch of CNOOC (China) Co., Ltd) | Han, Xiaodong (CNOOC Ltd and China University of Petroleum, Beijing)
Abstract Performance prediction is one of the important contents of oilfield development. It is also an important content affecting investment decision-making, especially for offshore oilfields with large investment. At present, most oilfields in China have entered high water cut stage or even extra high water cut stage, which requires higher prediction accuracy. Water drive curve is an important method for predicting performance. Traditional methods are based on exponential formulas, but these methods have poor adaptability in high water cut period. Because traditional methods deviate from straight line in high water cut period. In this paper, a robust method for predicting performance of offshore oilfield in high water cut period based on big data and artificial intelligence is proposed. Firstly, the reasons for the "upward warping" phenomenon of traditional methods deviating from the straight line are analyzed. It is found that the main reason for the deviation is that the relationship between the relative permeability ratio of oil to water and the water saturation curve no longer conforms to the exponential relationship. So a new percolation characteristic characterization equation with stronger adaptability is proposed, which focuses on the limit of high water flooding development. On this basis, the equation of the new water drive characteristic curve is deduced theoretically, and the dynamic prediction method is established. What's more, the solution of the method is based on large data and AI algorithm. This method has been applied to many high water flooding phase permeability curves, and the coincidence rate is more than 95.6%. The new water drive characteristic curve can better reflect the percolation characteristics of high water cut reservoirs. At the same time, the performance of adjustment wells and measures on the curve of development dynamic image is analyzed. Curve warping indicates that adjustment wells or measures are effective. Field application shows that the prediction error of the new method is less than 6%, which is more in line with the needs of oilfield development. Because of the application of artificial intelligence algorithm, the application is more convenient and saves a lot of time and money. This is a process of self-learning and self-improvement. As the oil field continues over time, each actual data will be recalculated into the database. Then the fitting and correction are carried out, and then the solution is learned again. This method has been applied to several oil fields in Bohai. And the effect is remarkable, which provides a good reference for the development of other oil fields.
Abstract Abundant faults, long oil-bearing intervals (up to 500m), and diverse fluids including conventional oil and heavy oil, result in P oilfield became one of the most complex oil fields in the Bohai Bay. The main characters ofinitial development plan are directional well with commingle production, open hole completion, large draw down, high oil production rate, and reverse nine-point well pattern. At present, the oilfield has entered a stage of high water cut, with average water cut more than 85%. What can we do next, decommissioning or rebirthing? An integrated solution was proposed to redevelop the oilfield which focus on the layers’ subdivision, the fine description of the sand body,a large number of horizontal wells on the top of the water-flooded layer are used to tap the potential, increase the water injector to transform the stream lines and rebuild the reservoir pressure, and search for potential sand bodies to increase reserves.
Yu, Chuan (The Research Institute of Petroleum Exploration and Development Petrochina) | Yang, Qinghai (The Research Institute of Petroleum Exploration and Development Petrochina) | Wei, Songbo (The Research Institute of Petroleum Exploration and Development Petrochina) | Li, Ming (The Research Institute of Petroleum Exploration and Development Petrochina) | Fu, Tao (The Research Institute of Petroleum Exploration and Development Petrochina)
Abstract Single-layer water cut measurement is of great significance for identifying and shutting off the unwanted water, analyzing oil remained and optimizing production. Currently, however, only the water cut of multilayer mixture can be measured by testing samples taken from wellhead, a way which is widely used in oilfields. That of single-layer fluid cannot be determined yet To address the problem, this paper puts forward a new impedance sensor that offers long-term online monitoring of single-layer water cut. This sensor is based on the different electrical conductivity of oil and water. It has two layers. The inner one contains three electrodes - two at both sides sending sinusoidal excitation signals and one at the middle receiving signals that have been attenuated by the water-oil medium. With the Maxwell's model of oil-water mixed fluid, the receiver then can measure the water cut online. The outer layer of the sensor is made of PEEK, an insulative protection. In front of the electrodes lies a static mixer which makes the measurement more accurate by fully blending the two media when they flow through the electrodes. Laboratory tests are carried out with the prototype of the sensor at various oil-water mixing ratios, fluid flow rates, and temperatures. Results show that the average margin of error is within ± 3%. Higher accuracy is seen when high water cut and flow rate enable oil globules to disperse more evenly and the space in between to get wider and the RMS error is less than 2%. If the water cut drops below 80%, the aggregation of the droplets will cause wild fluctuation and more errors in the measurement. In addition, the mineralization of the mixture directly changes its conductivity, which largely impacts the result. Meanwhile, temperature can influence the ionic movement intensity and then alter the conductivity of the medium. Therefore, in practice, the sensor calibration needs to be performed according to the range of medium salinity, and the temperature of the medium is collected in real time for temperature compensation. It is shown that after the adjustment, the water cut measurement results have higher accuracy and consistency. The impedance sensor can realize online water cut monitoring for a single-layer, indicated by tests. It is more suitable for the increasing high water cut oilfields in that it is more accurate as the water cut grows.