Waterflood Field Research Articles

A Fast History-Matching and Optimization Tool and Its Application to a Full Field with More than 1,000 Wells

Summary In this work, we study a waterflood field containing more than 1,000 wells, and the modern field management techniques with full-fidelity 3D geocellular reservoir models become computationally prohibitive. To overcome the difficulty, we developed a novel flow-network data-driven model—the general-purpose simulator-powered network (GPSNet) model—and used it for rapid history matching and optimization. GPSNet includes physics, such as mass conservation, multiphase flow, and phase changes, while maintaining a good level of efficiency. To build such a model, a cluster of 1D connections among well completion points is constructed and forms a flow network. Multiphase fluid flow is assumed to occur in each 1D connection, and the flow in the whole network is simulated by our in-house general-purpose simulator. Next, to effectively reduce the uncertainty, a hierarchical history-matching workflow is adopted to match the production data. Ensemble smoother with multiple data assimilation (ESMDA) plays an important role in reducing the error at each history-matching step. After that, the best-matched candidate is selected for numerical optimization to maximize field oil production with constraints satisfying field conditions. Excellent history-matching results have been achieved on the field level, and good matches have also been observed for key producers. It is also worth mentioning that the history-matching process took a mere 4 hours to finish 1,100 simulation jobs. The successful application of the GPSNet to this waterflood field demonstrates a promising workflow that can be used as a fast and reliable decision-making tool for reservoir management.

Two-phase flow thermo-hydro-mechanical modeling for a water flooding field case

Simulation of subsurface energy system involves multi-physical processes such as thermal, hydraulical, and mechanical (THM) processes, and requires a so-called THM coupled modeling approach. THM coupled modeling is commonly performed in geothermal energy production. However, for hydrocarbon extraction, we need to consider multiphase flow additionally. In this paper, we describe a three-dimensional numerical model of non-isothermal two-phase flow in the deformable porous medium by integrating governing equations of two-phase mixture in the porous media flow in the reservoir. To account for inter-woven impacts in subsurface conditions, we introduced a temperature-dependent fluid viscosity and a fluid density along with a strain-dependent reservoir permeability. Subsequently, we performed numerical experiments of a ten-year water flooding process employing the open-source parallelized code, OpenGeoSys. We considered different well patterns with colder water injection in realistic scenarios. Our results demonstrate that our model can simulate complex interactions of temperature, pore pressure, subsurface stress and water saturation simultaneously to evaluate the recovery performance. High temperature can promote fluid flow while cold water injection under non-isothermal conditions causes the normal stress reduction by significant thermal stress. Under different well patterns the displacement efficiency will be changed by the relative location between injection and production wells. This finding has provided the important reference for fluid flow and induced stress evolution during hydrocarbon exploitation under the environment of large reservoir depth and high temperature.

Technology Focus: EOR Operations (November 2023)

We often see and, in some very unfortunate cases, experience ravaging wildfires, colossal floods, and scorching droughts. These “once-in-a-lifetime” climate events have become increasingly commonplace. The World Health Organization has referred to climate change as “the biggest health threat facing humanity.” The finger is often pointed at the oil and gas industry as the source of these tragic events. Indeed, according to the International Energy Agency, oil companies emit more than 5,000 million tons of CO2 every year. Even so, seeing organizations pitted against the industry and our livelihoods can be disheartening, especially because we know the other half of the story that is overlooked but cannot be understated. Oil is the bedrock on which modern society is built. The primary question remains: How can we continue to produce oil while minimizing its climate‑harming byproducts? Thanks to the ingenuity of industry professionals around the world, new technologies are emerging that allow us to achieve this goal. Using these technologies, we can simultaneously maximize CO2 sequestration and oil recovery. By using surfactant-alternating-gas or surfactant/CO2 coinjection processes, oil production and CO2 storage can be tailored to the needs of a specific reservoir, as discussed in paper SPE 212969. The same industry that produces the building blocks for life‑saving medical prosthetics can now also recycle the plastic pollutants accumulating in our landfills and oceans. Using a combination of pyrolysis, chemical functionalization, and pulverization, Janus carbon nanofluids can be mass-produced from waste plastics. Under simulated laboratory conditions, in even ultralow concentrations (0.01 wt% in brine), they can alter wettability and reduce oil/brine interfacial tension, as described in paper SPE 214799. And, while government regulations seek to limit new exploration and drilling, we now have better reservoir-management strategies and tools to continue to produce essential energy from reservoirs that are approaching their centenary. Data from the La-Sa-Xing Field in the Daqing Reservoir complex in China documents reservoir management over more than 50 years, including the maturation of polymer floods from the first small‑scale pilots in 1972 to fieldwide application, which continues to the present. A review of the field in paper SPE 215058 provides insightful guidance on well spacing, slug size, polymer chemistry, and profile modifications, among other aspects. These developments and more position the oil and gas industry as an essential player in the energy transition. Recommended additional reading at OnePetro: www.onepetro.org. SPE 212949 Kuparuk Field Reservoir Management After 40 Years by Trond B. Jensen, ConocoPhillips, et al. SPE 212958 Accurate Horizontal Well Placement in Waterflooded Field’s Drilling Project: A Case Study From Central Sumatra Basin, Indonesia by Dwiki Fimadoni, Halliburton, et al. URTeC 3870505 Design of Chemical EOR in Unconventional Reservoirs by Johannes O. Alvarez, Chevron, et al.

A REVIEW STUDY ON AN INTEGRATED METHOD FOR SOLVING PROBLEMS ASSOCIATED WITH THE RE-DEVELOPMENT OF WATERFLOODED FIELDS

A REVIEW STUDY ON AN INTEGRATED METHOD FOR SOLVING PROBLEMS ASSOCIATED WITH THE RE-DEVELOPMENT OF WATERFLOODED FIELDS

Capacitance Resistance Clustered Model for Mature Peripheral Waterflood Performance Prediction & Optimization

Optimizing water injection rate distribution in waterflooding operations is a vital reservoir management aspect since water injection capacities may be constrained due to geographic location and facility limitations. Traditionally, numerical grid-based reservoir simulation is used for waterflood performance evaluation and prediction. However, the reservoir simulation approach can be time-consuming and expensive with the vast amount of wells data in mature fields.
 Capacitance Resistance Model (CRM) has been widely used recently as a data-driven physics-based model for rapid evaluation in waterflood projects. Even though CRM has a smaller computation load than numerical reservoir simulation, large mature fields containing hundreds of wells still pose a challenge for model calibration and optimization. In this study, we propose an alternative solution to improve CRM application in large-scale waterfloods that is particularly suitable for peripheral injection configuration. Our approach attempts to reduce CRM problem size by employing a clustering algorithm to automatically group producer wells with an irregular peripheral pattern. The selection of well groups considers well position and high throughput well (key well). We validate our solution through an application in a mature peripheral waterflood field case in South Sumatra. Based on the case study, we obtained up to 18.2 times increase in computation speed due to parameter reduction, with excellent history match accuracy.

Improving the quality of production simulation model by applying the results of nonlinear signal processing methods

The petroleum production simulation model is a reliable and commonly used tool by petroleum engineers in field operation and management. Production history matching is a vital link while building and completing the simulation model such that it accurately reflects reservoir behavior. In addition to the methods such as direct modification and automatic/assisted history matching, the authors propose a solution to improve the efficiency of history matching by applying the results of nonlinear signal processing methods and data point mapping method through interpolation algorithm. The method is applied for 3 water injection wells, 10 production wells at Miocene reservoir of the water flooding field X in Cuu Long Basin. The results show that the water-cut parameter of 7/10 production wells really improved in comparison to the initial model. The error of oil and liquid cumulative production in the simulation model compared to reality data respectively decreases from -2.8% to -0.3% and from +11.7% to less than 5%.

Stochastic multi-objective optimization approaches in a real-world oil field waterflood management

Multi-objective differential evolution with hybrid local dynamic search algorithm (HMODE-DLS) and non-dominated sorting genetic algorithm (NSGA-II) are applied successfully in a reservoir sector model of a Middle Eastern real-world oil field under waterflood development. The Pareto solutions of the two objectives of maximum oil production and minimum water production obtained by the two algorithms are analyzed and compared in this study. The sector model consists of four oil producers and three water injectors and it is run for ten years with twenty time-steps of six months each. A total of 140 decision variables are defined as bottom-hole pressures for the four producers and water injection rates for the three water injectors at each time step (i.e. 7 variables by 20 time-steps). The optimal Pareto solution is obtained at 12,600 function evaluations by HMODE-DLS with 70% convergence improvement compared to 42,000 objective evaluations by NSGA-II. Results show that NSGA-II generated more optimum solutions in the lower range (i.e. less than 480 thousand m3 (Mm3) total oil production) whereas, the hybrid MODE-DLS has a more optimum solution in the higher range of the Pareto front. The net flow method (NFM) is usedin this study to select the best optimal solutions from the Pareto front solutions based on the weight of the objective function chosen by the decision-maker. By using the entropy weight criteria, the best optimal solution of high oil production determined is 540.45 Mm3 at the HMODE-DLS Pareto front. On the other hand, the best optimal solution of low oil production obtained is 469.93 Mm3 at the NSGA-II Pareto front. The combined optimal Pareto fronts obtained by NSGA-II and HMODE-DLS algorithms offer good spread and diverse solutions for the decision-maker to select and operate the field based on the operation conditions and constraints.

A Flownet-Based Method for History Matching and Production Prediction of Shale or Tight Reservoirs with Fracturing Treatment

Summary Based on a newly developed physics-based data-driven model FlowNet, this paper presents an effective method for history matching and production prediction of fractured shale or tight reservoirs without any prior information about fracture geometry. In this method, four types of well nodes including fracturing cluster nodes, fracture nodes, stimulated reservoir volume (SRV) nodes, and matrix nodes are allocated in the reservoir. Then, the reservoir model is simplified as a flow network composed of some 1D connection elements between these nodes. Some grids are divided on each connection element, and the grids on the same connection element are of equal width and permeability. Subsequently, a fully implicit nonlinear solver is used to solve flow equations in this FlowNet grid system to obtain pressure, phase saturation, and production rates, etc. Efficient history-matching procedure based on the FlowNet model of the fractured reservoir is used to determine the parameters of connection elements, and then fast production prediction can be conducted. Five numerical examples including single-well depletion, waterflooding development with natural fractures, multiple-well interference, three-phase flow, and an actual waterflooding field case validate that this presented FlowNet-based method can achieve good history matching and production prediction for various flow problems in shale or tight reservoirs with fracturing treatment, and the history-matched transmissibility and volume of connection elements can reflect the existence of high-conductivity fractures.

Impact of sewage water irrigation on agricultural soil

The rapidly increasing population growth and the steady increase in water requirements for agricultural and industrial development have placed severe stress on the water resources available and the long term use of sewage water for irrigation highly affects soil properties. In this study soil samples were collected from a cauliflower field prior and after sewage water irrigation, and the impact of sewage water irrigation on physical, chemical, and biological properties of soil was compared. For this, tested were pH, Electrical Conductivity (EC), Organic Carbon, available Nitrogen, Phosphorus, Potassium, Calcium, Magnesium, Zinc, Iron, Copper, Manganese, and microbial activity. Soil microbial biomass carbon, basal soil respiration, total viable count of bacteria, coliform population, Pseudomonas species, and Azotobacter significantly increased after sewage water irrigation as compared to prior to irrigation. Nevertheless, the bulk density and Rhizobium species of the soil flooded with sewage water was decreased relative to the same characteristics prior to irrigation. Cauliflower yield was significantly increased when sewage water flooded field as compared to the tube well water flooded field (i.e., water delivered via an iron pipe). Escherichia coli contamination was greater in sewage water and groundwater that can pose health risks for the nearby communities, to farmers and consumer of farm products. Hence, the efficient use of sewage and municipal wastewater successfully increase water resource for irrigation and may help in expanding agricultural production. But excessive use of sewage water may also affect the soil flora and fertility.

Fast History Matching and Optimization Using a Novel Physics-Based Data-Driven Model: An Application to a Diatomite Reservoir

SummaryFull-physics models in history matching (HM) and optimization can be computationally expensive because these problems usually require hundreds of simulations or more. In a previous study, a physics-based data-driven network model was implemented with a commercial simulator that served as a surrogate without the need to build a 3D geological model. In this paper, the network model is reconstructed to account for complex reservoir conditions of mature fields and successfully apply it to a diatomite reservoir in the San Joaquin Valley, California, for rapid HM and optimization.The reservoir is simplified into a network of 1D connections between well perforations. These connections are discretized into gridblocks, and the grid properties are calibrated to historical production data. Elevation change, saturation distribution, capillary pressure, and relative permeability are accounted for to best represent the mature field conditions. To simulate this physics-based network model through a commercial simulator, an equivalent Cartesian model is designed where rows correspond to the previously mentioned connections. Thereafter, the HM can be performed with the ensemble smoother with multiple data assimilation (ESMDA) algorithm under a sequential iterative process. A representative model after HM is then used for well control optimization.The network model methodology has been successfully applied to the waterflood optimization for a 56-well sector model of a diatomite reservoir in the San Joaquin Valley. HM results show that the network model matches with field level production history and gives reasonable matches for most of the wells, including pressure and volumetric data. The calibrated posterior ensemble of HM yields a satisfactory production prediction that is verified by the remaining historical data. For well control optimization, the P50 model is selected to maximize the net present value (NPV) in 5 years under provided well/field constraints. This confirms that the calibrated network model is accurate enough for production forecasts and optimization. The use of a commercial simulator in the network model provided flexibility to account for complex physics, such as elevation difference between wells, saturation nonequilibrium, and strong capillary pressure. Unlike the traditional big-loop workflow that relies on a detailed characterization of geological models, the proposed network model only requires production data and can be built and updated rapidly. The model also runs much faster (tens of seconds) than a full-physics model because of the use of much fewer gridblocks.To our knowledge, this is the first time this physics-based data-driven network model is applied with a commercial simulator on a field waterflood case. Unlike approaches developed with analytic solutions, the use of a commercial simulator makes it feasible to be further extended for complex processes (e.g., thermal or compositional flow). It serves as a useful surrogate model for both fast and reliable decision-making in reservoir management.

Analytical Rate-Transient Analysis and Production Performance of Waterflooded Fields with Delayed Injection Support

SummaryAn approach to the analysis of production data from waterflooded oil fields is proposed in this paper. The method builds on the established techniques of rate-transient analysis (RTA) and extends the analysis period to include the transient- and steady-state effects caused by a water-injection well. This includes the initial rate transient during primary production, the depletion period of boundary-dominated flow (BDF), a transient period after injection starts and diffuses across the reservoir, and the steady-state production that follows. RTA will be applied to immiscible displacement using a graph that can be used to ascertain reservoir properties and evaluate performance aspects of the waterflood. The developed solutions can also be used for accurate and rapid forecasting of all production transience and boundary-dominated behavior at all stages of field life.Rigorous solutions are derived for the transient unit mobility displacement of a reservoir fluid, and for both constant-rate-injection and constant-pressure-injection after a period of reservoir depletion. A simple treatment of two-phase flow is given to extend this to the water/oil-displacement problem.The solutions are analytical and are validated using reservoir simulation and applied to field cases. Individual wells or total fields can be studied with this technique; several examples of both will be given. Practical cases are given for use of the new theory. The equations can be applied to production-data interpretation, production forecasting, injection-water allocation, and for the diagnosis of waterflood-performance problems.

Waterflood optimization using an injector producer pair recovery factor, a novel approach

This paper presents an approach to optimize the recovery factor and sweep efficiency in a waterflooding process by automating the optimum injection rate calculations for water injectors using streamline simulation. A streamline simulator is an appropriate tool for modern waterflood management and can be used to determine the dynamic interaction between injector and producer pairs, which will vary over time based on sweep efficiency and operational changes. A streamline simulator can be used to identify injectors, which are not supporting production and contributing mainly to water producing wells. Streamlines illustrate natural fluid-flow paths in the reservoir, which are based on fluid properties, rock properties, well distribution and well rates across the reservoir. A bundle of connected streamlines can provide the oil in place between an injector/producer pair at any given time during a simulation run. Thus, the well pair recovery factors for each injector/producer pair, the produced water cut and the weighting factor for each injector are determined. Multiplying this weighting factor by the injection rates determines the new injection rate for each injector. For a well pair water cut that is lower than the average field water cut, the injection rate will be increased and vice versa. Given a finite volume of injection water, there will be a re-allocating of water from a well pair with a low recovery factor and high water cut and redistributing the water to injectors supporting low water cut producers, thus maximizing the recovery factor and reducing the field water production. The described approach is an automated procedure during the reservoir simulation run, making it appropriate for full field waterflood optimization with many injectors and producers in high-resolution heterogeneous brown reservoirs. This approach can reduce the water cut and increase the recovery factor and extend the life of the waterflooded oil fields. It was initially tested with a synthetic model and later with an actual reservoir model, which will be described in this paper.

Analytical Work Flows Enable Continuous Waterflooding Optimization for a Mature Field

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 198586, “A New Continuous Waterflood Operations Optimization for a Mature Oil Field by Use of Analytical Work Flows That Improve Reservoir Characterization,” by Atul Yadav and Anton Malkov, SPE, Wintershall, and Essam Omara, Suez Oil Company, et al., prepared for the 2019 SPE Gas and Oil Technology Showcase and Conference, Dubai, 21–23 October. The paper has not been peer reviewed. In the complete paper, the authors present a novel approach that uses data-mining techniques on operations data of a complex mature oil field in the Gulf of Suez that is currently being waterflooded. Evidence is presented about how salinity data can be used to further justify the linkages between different wells obtained from cross-correlation analysis. The results presented in this research can be adapted to any waterflooded field to optimize recovery at frequent intervals where injection and production data are available continuously. Introduction Mature oil fields typically present challenges of increased water production and water handling. Considering the geological complexity and associated field-performance behavior, reservoir characterization to optimize water flooding is a major challenge. An integrated reservoir study was con ducted to minimize reservoir uncertainties and increase understanding of the field’s performance behavior. The acceptable history-matched model was used to estimate remaining oil potential, maintain and increase current production levels, and optimize the water-injection rate. Generally, history-matched models need to be updated throughout the life of producing fields as new subsurface data are acquired. Such integrated reservoir modeling studies, however, can be time-consuming and do not necessarily enable quicker decision-making around operational activities. The continuous recording of production and injection data presents new opportunities to apply novel analytical techniques to understand interwell connectivity in the reservoir. The current ability to store and analyze data, coupled with advances in the ability to interpret big data sets, has helped create an independent toolkit that provides analysis without the geological model. In addition, geological information such as pre-existing faults and the commingled or disconnected nature of production between different layers can be integrated to obtain and improve analyses from the analytical models. The authors analyze the results using Pearson’s cross-correlation analysis measure to obtain a qualitative analysis of the field. They also apply Spearman’s rank correlation analysis for the discussed field (henceforth named GOS for purposes of this paper) that helps compare injection and production data. The objective is to present a comparison between the analytical and the stream-lined approach to show consistency in reservoir characterization. The effective injector/producer pairs identified form an important component of the field development.

Identification and characterization of Thermally Induced Fractures through integrated analytical and semi-analytical models

Thermally induced fractures (TIFs) are common in waterflooded fields where the injection of (relatively) cold water leads to a cooling front that reduces a formation's in-situ stresses. Understanding TIFs is important since their existence impacts oil recovery potential, well injectivity, injection well integrity, and injector-producer well spacing in reservoirs under waterflooding. Identifying and characterizing dynamic TIF growth is a critical step in defining field development strategies and making daily reservoir management decisions. This research introduces a workflow that integrates analytical well monitoring and semi-analytical models to identify TIF onset, propagation properties, direction, and impact during dynamic reservoir events occurring at different levels. The practicality of the proposed workflow has been tested using synthetic data and its robustness confirmed by an analysis of actual field data. The novelty of the approach presented here is in its efficient integration of recent analytical and semi-analytical models to identify TIF onset, propagation, characteristics, and impact from generally available well injection production history data. This practical workflow will help engineers detect and monitor TIFs and evaluate the metrics describing waterflood performance, including flood efficiency, inter-well communication, and pressure maintenance.

Water Flooding Timing Research and Field Practice in Light Oil Reservoir

Water flooding timing is the research focus in the process of reservoir development, especially for offshore reservoir, reasonable water flooding timing can ensure better development effect, at the same time, it can save the investment cost in the process of reservoir development, so as to achieve sustainable and efficient development of offshore oilfield. At present, there are many researches on the flooding timing of conventional heavy oil reservoir, but few on the flooding timing of light oil reservoir. In order to clarify the development effect of light oil reservoir under different water flooding timing, taking offshore oilfield A as an example, combining with numerical simulation technology and reservoir engineering analysis method, the development effect under different water flooding timing is analyzed. The results show that when the reservoir pressure drops to half of the saturation pressure, the development effect of water flooding for light oil reservoir is the best. Therefore, the water flooding time can be postponed for the light oil reservoir with high porosity and permeability. The research results are applied to the actual development case of oilfield A. The practice shows that water flooding in the late development stage of light oil reservoir can effectively prolong the water-free oil production period, improve the initial oil recovery rate, reduce the initial development investment, thus effectively shorten the investment recovery period and improve the development effect of the reservoir in the whole life production cycle.

Optimizing water shut off (WSO) by utilizing cross-linker additive system in the nearby wellbore treatment in sandstone environment

Excessive water production is one of the biggest problems commonly found in the brown water-flood field. There are two treatments of water shut-off (WSO) in hydrocarbon wells. The mechanical WSO is a routine operation that is commonly carried out and is part of standard well work; meanwhile, the chemical WSO is a specific treatment. The study aims to identify the effect of polymer concentration, injection rate, and soaking time on the effectiveness of chemical WSO with cross-linked polymers in a specific field. The study proposes and analyses the optimization of this treatment in the 7E Sandstone field by utilizing a conceptual simulation model. Geographically, this field is located in the Central Sumatera basin. The field is a moderately homogenous sandstone. Last decade, the 7E field was associated with excessive water production issue, some mechanical WSO has been done to solve the problem, but less effective and inefficient. Hence chemical WSO job comes as a promising option to overcome this problem robustly. The cross-link polymer injection treatment is the action of blocking water from entering and reaching production wells by using a mixture of polymer, cross-linker, and water. A base case of the conceptual model has been developed, then over twenty injection scenarios wide-ranging based on polymer concentrations are implemented in the model. Each of these concentration schemes is simulated using different injection flow rates for the total injection volume of 2000 bbl. The injection rate sets at 1000 bbl/day for twice injection and 2000 bbl/day for one injection. Soaking time is settled for one, two, and three days to give time for generating gelatin. A comparison of water production before and after the WSO is used to investigate WSO effectivity. The simulation result mentions that the WSO implementation can decrease excess water from 385,143 bbl to 186,189 bbl.

Practical Reservoir-Management Strategy To Optimize Waterflooded Pools With Minimum Capital Used

SummaryIn this consistently low–oil–price environment, where infill drilling and new field developments struggle to meet economic metrics, production optimization continues to be a focus and driver for the industry. Currently, waterflooding contributes significantly to global oil production and is one of the main nonthermal techniques that can be applied to increase pool recovery. Although proper reservoir management of assets under waterflood (WF) is critical to reaching the highest recovery factor (RF) possible, it is difficult to achieve and maintain given the inherently dynamic nature of the production mechanism. Further, to achieve optimal reservoir management while providing the opportunity to leverage alternative enhanced–oil–recovery (EOR) technology, the existing subsurface and surface infrastructure should be fully optimized. Optimizing the subsurface and surface infrastructure in parallel with achieving optimal reservoir management will result in higher capital efficiency while improving key economic metrics such as operating costs (Opcost); reserves–replacement ratio; depreciation, depletion, and amortization; and overall earnings. Given the existing challenges that include reservoir–conformance problems, lack of reservoir energy, excess fluid production, wellbore/pipeline–integrity issues, and infrastructure constraints, how to fully optimize the current infrastructure while achieving optimal reservoir management in parallel is the main question and challenge.Husky Energy's medium–oil–reservoir–management strategy has been highly successful in reinforcing WF as a sustainable long–term recovery method. In this paper we will present a practical workflow to tackle the challenges highlighted by using a systematic reservoir/production–engineering approach with minimum additional capital expenditure (Capex). First, a robust framework was developed to answer three main questions: What is happening?, Why is it happening?, and How can it be improved? Then, a comprehensive dynamic surveillance methodology, consisting of both numerical and analytical techniques and a 10–step workflow for optimizing a WF project, is discussed. This is followed by the results achieved by using this strategy in three WF fields: the Wainwright Sparky, Wildmere Lloydminster, and Marsden–Manitou Sparky pools in the Lloydminster oil block. The positive effect that this reservoir–management process has had on all key financial metrics will be discussed. As an example, since the beginning of the optimization initiative, the Wainwright and Wildmere pool production has increased 21 and 23%, respectively, and the Opcost has decreased by 33 and 42%, respectively. Further, since implementing a similar strategy in 2016 at the Marsden–Manitou WF, its production has increased by 30% and its Opcost has decreased by more than 18%. Finally, we will present a WF–protocol checklist that has been developed as a guideline for engineers who need to optimize pool performance even in a capital–constrained environment.

Increasing confidence in full field modelling and water flood planning for a giant reservoir under primary depletion through Material Balance modelling

One of the principle inputs to project economics and all business decisions is a realistic production forecast and a practical and achievable development plan (i.e. waterflood). Particularly this becomes challenging in supergiant oil fields with medium to low lateral connectivity. The main objectives of the Production Forecast and feasibility study for water injection are:1- Provide an overview of the total expected production profile, expected wells potential/spare capacity, water breakthrough timing and water cut development over time2- Highlight the requirements to maintain performance, suggest the optimum development pattern3- Increasing confidence in business decisions to develop the reservoir in questionThe main tool used for these purposes is a sophisticated reservoir simulation software, namely CMG©, since it can predict reservoir behavior, honor physical constraints and capture the heterogeneity within the reservoir to accurately predict performance. However, the starting point for this kind of complicated studies needs to start from the basics, in order to understand the big picture and be able to plan properly for the scope to be delivered, hence, utilizing analytical tools like MBAL becomes quite necessary, if not crucial, to the success of full field modelling and choosing an optimum water flood pattern and design.This paper covers the methodology for building the reservoir component utilizing a Material Balance model, of which the results will be used as an input to reservoir simulation to evaluate and accurately predict reservoir performance, which directly feeds into planning for water flooding projects and selection of an optimum flood pattern.A Tank model was built at first to assess and understand the driving forces (energies) of the reservoir in question, utilizing pressure and production data from legacy wells, the prepared model is also supported by geological and petro physical studies to give representative results. Acquired Static Bottom Hole Pressures (SBHPs) in wells were used as anchor points for the tank pressure and to test the validity of the history match. Multiple analytical methods to QC the results and STOIIP volume were conducted, e.g. the Havlena-Odeh method.This methodology has been tested successfully in the stated super giant oil field, in which the reservoir in question is a carbonate rock formation. An example of this is covered in the paper. It was concluded that utilizing a history matched and coherent MBAL model before conducting a detailed reservoir simulation study can save a lot of time and effort by providing guidance to the path which needs to be followed, and sheds light on the critical elements to be looked after. This has also helped to uncover the driving mechanisms and energies in the reservoir, hence allowing the engineer to plan for the necessary voidage replacement and water injection rates to sustain the reservoir pressure and pattern development. Another technical advantage of the described method is the higher sustainability of the model.The suggested method, in combination with geological and petro physical information available, can be applied to majority of the reservoirs. This combination is paramount to ensure optimum time and planning that is followed for each reservoir development study that involves water flooding.

Best Practices for Waterflooding Optimization Improve Oil Recovery in Mature Fields

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 186431, “Waterflooding Optimization: A Pragmatic and Cost-Effective Approach To Improve Oil Recovery From Mature Fields,” by X.G. Lu, SPE, and J. Xu, C&C Reservoirs, prepared for the 2017 SPE/IATMI Asia Pacific Oil and Gas Conference and Exhibition, Bali, Indonesia, 17–19 October. The paper has not been peer reviewed. Most mature sandstone reservoirs feature natural aquifer drive, artificial water drive, or a combination of the two. These mature fields generally are characterized by high water cut and high recovery efficiency. This paper presents technologies and best practices to improve oil recovery in mature fields through waterflooding optimization. These technologies have proved practical and cost-effective. Introduction Although chemical enhanced-oil-recovery (EOR) technologies such as polymer flood and alkali/surfactant/polymer (ASP) flood can improve oil recovery by 10 and 20%, for waterflooded sandstone reservoirs, respectively, they are expensive and are not applicable in most mature fields at a low oil price. A major problem for waterflooded fields is that, with increased water/oil ratio (WOR), the cost of processing produced fluid soars to exceed the breakeven mark. As a result, many wells are forced to be shut in; in some instances, the entire field may be suspended. Waterflooding-Optimization Methods The technologies discussed in this section are effective generally for multilayer, heterogeneous sandstone reservoirs with high permeability contrast. Zonal Water Injection. This is the most widely applied water-injection-optimization technology. In a multilayered reservoir, early water encroachment along thief zones often occurs. During the mature stage, when the field produces at high water cut, commingled water injection usually leads to ineffective water cycling from the injectors, flowing preferentially through the high-permeability thief zones and back to the surface from the producers. Using the same injecting wellbore, zonal water injection can enhance water-injection rate arbitrarily in low-permeability, low-production, and low-water-cut production zones while reducing the water-injection rate of medium-high permeability, high-water-cut production zones. Thus, the application of this technology can achieve the goal of expanding sweeping efficiency in order to improve oil recovery. Changing the Direction of Fluid Flow. The basic principle is to change the originally fixed injection/production-fluid-flow direction to sweep the remaining oil in bypassed high-oil-saturation areas. This goal is achieved through converting injectors into producers or vice versa. In practice, some injectors are shut in while others are left inactive or regular conversion between injectors and producers is conducted in order to change fluid-flow direction, achieving expanded sweep efficiency. Water Shutoff To Improve Areal Sweeping Volume. This application addresses the challenge of lateral heterogeneities resulting from the permeability contrast of various facies sands. This technique seeks to change the original areal waterflooding direction to constrain ineffective water injection by shutting in the high-fluid-production, high-water-cut wells. The change in liquid-flow direction will benefit the injected water turning to the poorly swept region or bypassed remaining oil to expand sweep volume, achieving the goal of improved ultimate recovery.

An approach to waterflood optimization: case study of the reservoir X

Over the years, waterflooding has been the most widely used secondary oil recovery method after the exhaustion of the primary depletion energy of the reservoir. Waterflooding schemes have to be planned such that at every point of the operation, net income from oil recovery exceeds operating expenditure of which produced water disposal cost is paramount. Hence, engineers are regularly plagued with challenges such as optimal completions zones for injectors and producers, optimal flood pattern to adopt and number/type of producers and injectors to use in waterflood field development so as to improve oil recovery, but reduce water production. The aim of this study is to optimize waterflooding from a case study model using reservoir simulation techniques. A simple optimization methodology involving the analysis of the effects of zones of production and injection, pattern of waterflood selected and number/type of producers and injectors on cumulative recovery from a waterflooded reservoir was used. Results revealed that (1) pressure maintenance/increment is more effective when there is water injection into more zones of the reservoir, (2) for waterflood operations involving the use of vertical injectors, higher water production was observed because water is expected to flow more conveniently in the upward direction due to gravity rather than laterally and (3) with horizontal injectors, higher cumulative production was achieved especially for cases where water is injected into the same zones from which oil is produced.