Waterflood Management Research Articles

Advances in Monitoring and Understanding the Dynamics of Suspended-Sediment Transport in the River Drava, Slovenia: An Analysis More than a Decade-Long

Managing sediment transport in streams is crucial to the surface water resource development strategy and has several implications for flood risk and water management, hydropower use, and balancing river morphology. This paper summarises the movement and behaviour of suspended sediment within the Slovenian portion of the River Drava, covering a span of thirteen years from 2005 to 2018. An analysis of relevant data collected during this period is also presented. Suspended-sediment dynamics strongly depend on flow velocity, seasonal variations in sediment sources, and human interventions in the riverbed. The transportation of material in the River Drava results in the accumulation of sediments in reservoirs and riverbeds, consequently impeding the natural hydrological cycle by reducing the outflow into aquifers. The 2018 high-water event is analysed in terms of the dependence of concentration of suspended sediments on discharge, where counterclockwise hysteresis was observed, providing an essential clue to the origin of sediment. Sediments from the River Drava in Slovenia are managed with some conventional processes and are mainly deposited or reintegrated into rivers and aquatic ecosystems. Some additional sediment management strategies with long-term solutions for efficient and comprehensive water management, hydropower, and ecological problems are proposed.

Green Infrastructure: Flood Control and Water Management

Water scarcity is a pressing issue in many parts of the world. One innovative solution to this problem is rainwater harvesting, which involves collecting and storing rainwater for later use. The study aims to install a rainwater harvesting and treatment system to :1. Reduce water loss by its running-off.2 Meeting the demands of increasing water. 3. Reducing groundwater contamination.4. Increase available water during dry season.5. Reduce flooding and potentially prevent flooding of roads. This is a descriptive research method and is purely qualitative. It used Focus Group Discussion (FGD), Interview, and secondary data to get the necessary information from three Consultants, three Executives, and four Professors who are experts in the field. The study found that the rainwater harvesting and treatment facility would be a feasible project. It would minimize water consumption costs and reduce flooding in the city, with potential for replication by other universities, governments, and private entities.

Development of intelligent system operational maintenance of the level of oil and gas production and waterflooding management

This article discusses the development of an intelligent System for the operational maintenance of the level of oil and gas production as part of the implementation of the Strategy for the development of information technologies for data management and the Program for the development of digitalization of fields of JSC «NC Kazmunaigas». The advantage of the system is multitasking and using almost all the data coming from production facilities in real time. The main task of the system is to manage a group of wells taking into account their mutual influence to maximize oil production and reduce the negative impact of uncoordinated well operation without damaging the rational system of field development. A significant feature of the developed system is the creation of complex algorithms for predicting the main development indicators using artificial neural networks based on a combination of CRM (capacity resistance model), FFNN (neural network with direct communication), MBM (material balance model) and BFGS (Broyden-Fletcher-Goldfarb-Shanno algorithm) methods. During the pilot test on 10 wells, the modes were adjusted according to the recommendations issued by the system and the system confirmed its operability and effectiveness of application. Keywords: virtual flow meter; labor productivity; return distribution; machine learning; rational development system; neural networks.

Analisis Usahatani Perkebunan Kelapa Sawit Rakyat Berdasarkan Jasa Ekosistem Pengaturan Tata Aliran Air dan Banjir di Provinsi Riau

Riau Province has the largest oil palm plantation in Indonesia consisting of large national private plantations and community plantations located in various land typologies and landscapes. Each landscape has characteristics of forest areas and peat hydrological units that can affect the level of land productivity. This study aims to determine the carrying capacity of environmental capacity based on ecosystem services of water flow and flood management services in smallholder oil palm plantations in Riau Province. The analysis method consists of spatial analysis and farming analysis, spatial analysis to determine the carrying capacity of environmental capacity based on ecosystem services for water flow and flood management services. Farming analysis to determine land productivity, fresh fruit bunch (FFB) prices, production costs and farmer income based on environmental capacity criteria based on ecosystem services for water flow and flood management services. The results showed that based on the capacity of environmental capacity based on ecosystem services for water flow and flood management services on smallholder oil palm plantations in Riau Province consisted of very low, low, medium, high and very high criteria. Furthermore, the level of productivity, FFB prices, production costs and farmers' income are influenced by the typology of the capacity of water flow and flood management services. The higher the capacity of water flow and flood management services, the higher the land productivity and farmers' income.

Resilience in Urban and Architectural Design—The Issue of Sustainable Development for Areas Associated with an Embankment

The dynamically changing world poses new challenges to urbanized areas, e.g., related to water management in the architectural and urban context. Improving retention and strengthening blue-green infrastructure can be based on technical, semi-natural and natural methods, which are less invasive. Various forms are used in the city space: flow control, detention, retention, filtration, infiltration, and treatment. The implementation of the green order strategy and shaping sustainable development in the context of designing the city’s resilience is associated with shaping spatial policy and urban planning assumptions for the transformation of public spaces and new investments in urbanized areas in crisis. The shaping of waterfronts in the city and green and blue infrastructure significantly shape the parameters of the environment and the regenerative capacity of the urban ecosystem. The aim of this work was to show the relationship between the problem of embankments and the possibilities of developing space in their proximity, including areas exposed to the risk of flooding. The relationships determined by the goal were verified in comparative studies, a repeatable method of collecting, processing, analyzing, and interpreting the obtained data was used. The issue was presented in a broader context of flood risk and water management in the area of Lake Zegrze, collisions and spatial conflicts were analyzed. The results are presented in the context of detailed water management data for the complex of Riva Zegrze facilities, which is a model example regarding the sustainable development of areas on embankments, considering their specific floodplain development possibilities. The effects of the research allowed for the formulation of conclusions, including in terms of implementation, in the field of urban and architectural design for areas associated with an embankment.

Hybrid approach of using bi-objective genetic programming in well control optimization of waterflood management

A new hybrid optimization approach is proposed by applying bi-objective genetic programming (BioGP) algorithm along with NSGA-II algorithm to expand the diversity of the Pareto solutions and speed up the convergence. The novel methodology is used in two distinct cases: the benchmark model for the Brugge field and a Middle Eastern oil-field sector model. The Brugge field includes twenty producing wells and ten injecting wells, but the real sector model has three injectors and four producers. The two primary objectives applied are to optimize the total volume of produced oil and reduce cumulative produced water. In the optimization process, the injection rate (qwi) and the bottom-hole pressure (BHP) are the control parameters for injection and producing wells, respectively. The hybrid technique of applying BioGP guided NSGA-II in the Brugge field model demonstrated a 50% acceleration in the convergence speed when compared to the NSGA-II solution. The calculated Pareto solutions for the Middle-Eastern sector model by the proposed methodology at various generations exhibited better diversity and convergence in comparison to the NSGA-II solutions. The highest cumulative produced oil of 550.45 × 103 m3 is obtained by the proposed hybrid methodology in comparison to the NSGA-II's highest cumulative of 522 × 103 m3. The two solution points A′ and B′ achieved using the BioGP guided NSGA-II have lower WOR by 17% and 15%, respectively, than A and B solutions established by NSGA-II alone. Pareto solution ranking is performed using the net flow method (NFM) and the best optimum solution determined for BioGP guided NSGA-II is 532.38 × 103 m3 oil using equal-based weight compared to 505.44 × 103 m3 using the entropy-based weights of 41% oil & 59% water. Overall, the optimal Pareto solutions achieved by the proposed methodology of using BioGP guided NSGA-II algorithm has better diversity with improvement in convergence speed in comparison to the NSGA-II.

Open-Source Data Processing Chain for Marche Region X-band Weather Radar

In the framework of three projects co-funded by the European Union (EU), an X-band (8-12 GHz frequency range) polarimetric radar was installed in the Marche Region territory (East-Central Italy) at Cingoli municipality, province of Macerata. The radar site is located at about 750 m above sea level and about 30 km away from the Adriatic Sea. The radar, managed by the Marche Region Civil Protection Service, is employed for weather monitoring purposes and is in pre-operational stage. It is known that radar measurements are affected by various sources of error, to be addressed in order to improve the accuracy of final products. Among these, the most important are radar calibration, ground and sea clutter, beam blockage, rain attenuation, wet-radome attenuation, beam-broadening, non-uniform beam filling, vertical variability of precipitation and wireless local-area-network (WLAN) interferences. Nowadays quantitative rainfall estimation using X-band weather radar are essential to meet requirements for flood forecasting, water management and many hydro-meteorological applications. Besides higher resolution, X-band radars are cost-effective compared to S- or C-band radars because of smaller antenna size. On the other hand, main disadvantages of such systems are the large influence of attenuation by liquid water and a relatively short range. In this work, we will present the data-processing chain developed ad hoc in order to remove or at least reduce the sources of error affecting Cingoli radar data. The performance of the data-processing chain was evaluated in the light of case studies related to meteorological events that interested Marche region territory in the last two years. The software was developed using open source technology. The current version of the chain does not take into account the echoes from sea clutter and the attenuation due to wet radome that can be significant at X-band; such issues will be addressed in a future work.

The performance of streamline simulation technique to mimic the waterflooding management process in oil reservoirs

Multiple simulation techniques are often used to predict the performance of waterflooding and to plan the infill drilling techniques via a process called waterflooding management. However, such simulation techniques usually suffer from many drawbacks and shortages. Therefore, the waterflooding process management is in an evitable need for a robust technique, which can predict the optimal water injection rates and the incremental oil production in a cost-effective manner.In this study, the streamline simulation technique (SST) was used to visualize and analyze the fluid flow patterns in order to investigate the validity of this technique for improving waterflooding management process. In addition, the feasibility of SST in waterflooding management was clearly tested by setting new injection strategies to improve the sweep efficiency via estimating the injector-producer relationship as well as the water injection efficiency. Furthermore, the advantages of streamline simulation visualization in determining the best infill drilling locations, which production wells could be converted to injection wells, and optimizing water injection rates based on monitoring and trials were investigated. The results of this research indicated that the streamline simulation technique is capable to efficiently model and predict the waterflooding process. The SST is computationally efficient and fast in terms of providing flow visualization among injectors and producers, estimating an allocation factor for injection system, and optimizing the locations of new injectors/producers’ wells to increase the sweep efficiency. In addition, the SST could provide a deep understanding with visualization to the waterflooding process and how to improve the waterflooding in oil reservoirs. In this work, through the comparison of various waterflooding scenarios, we discovered the best solution that eliminated the need for optimization algorithms with high computational requirements. This approach relies on areas exhibiting low streamline densities to enable streamlined prediction of infill well locations, thereby reducing simulator processing time. Consequently, this method represents an effective first step in the process of identifying approximate infill well locations, and its efficacy can be enhanced by integrating optimization methods.

Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique

To ease water scarcity, dynamic programming, stochastic dynamic programming, and heuristic algorithms have been applied to solve problem matters related to water resources. Development, operation, and management are vital in a reservoir operating policy, especially when the reservoir serves a complex objective. In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD). Due to trade-offs between water supply and flood management, the HHO and OBL-HHO models have configurable thresholds to optimise the KGD reservoir operation. To determine the efficacy of the HHO and OBL-HHO in reservoir optimisation, reliability, vulnerability, and resilience are risk measures evaluated. If inflow categories are omitted, the OBL-HHO meets 71.49% of demand compared to 54.83% for the standalone HHO. The HHO proved superior to OBL-HHO in satisfying demand during medium inflows, achieving 38.60% compared to 20.61%, even though the HHO may have experienced water loss at the end of the storage level. The HHO is still a promising method, as proven by its reliability and resilience indices compared to other published heuristic algorithms: at 62.50% and 1.56, respectively. The Artificial Bee Colony (ABC) outcomes satisfied demand at 61.36%, 59.47% with the Particle Swarm Optimisation (PSO), 55.68% with the real-coded Genetic Algorithm (GA), and 23.5 percent with the binary GA. For resilience, the ABC scored 0.16, PSO scored 0.15, and real coded GA scored 0.14 whilst the binary-GA has the worst failure recovery algorithm with 0.09.

Integrate inter–well connectivity data with static reservoir models based on Bayesian formalism

The inter-well connectivity calculated from reservoir dynamic production data reflects formation heterogeneity quantitatively. Currently, the calculated inter-well connectivity between pair wells is mainly used as a tool for water flood management but not for quantitative reservoir characterization. This study proposes an innovative, dynamic data integration workflow that can integrate inter-well connectivity with a static reservoir model. In the workflow, the first step is calculating the inter-well connectivity vectors from the reservoir pairwise injector and producer wells. The second step covers interpolation in the domain of interest. The third step is to update the permeability model based on the Bayesian updating method. The result of this study shows that integrating the calculated inter-well connectivity with the static models enhances model reliability and it also provides an insight to deeper geological understanding reflected from dynamic data integration in reservoir modeling.

Eddy covariance assessment of alternate wetting and drying floodwater management on rice methane emissions

Reducing methane emissions and water use is critical for combating climate change and declining aquifers on food production. Reductions in irrigation water use and methane emissions are known benefits of practicing alternate wetting and drying (AWD) over continuous flooding (CF) water management in lowland rice (Oryza sativa L.) production systems. In a two-year (2020 and 2021) study, methane emissions from large farm-scale (∼50 ha) rice fields managed under CF and AWD in soils dominated by Sharkey clay (Sharkey clay, clay over loamy, montmorillonitic non-acid, thermic Vertic halauepet) were monitored using the eddy covariance method (EC). In the EC system, an open-path laser gas analyzer was used to monitor air methane gas density in the constant flux layer of the atmosphere over the rice-crop canopies. Total water pumped into the field for floodwater management was higher in CF compared to AWD by 24 and 14% in 2020 and 2021, respectively. Considerable variations between seasons in the amount of methane emitted from the CF and AWD treatments were observed: CF emitted 29 and 75 kg ha−1 and AWD emitted 14 and 34 kg ha−1 methane in 2020 and 2021, respectively. Notwithstanding, the extent of reduction in methane emissions due to AWD over CF was similar for each crop season (52% in 2020 and 55% in 2021). Rice grain yield harvested differed by only ±2% between AWD and CF. This investigation of large-scale system-level evaluation, using the EC method, confirmed that by practicing AWD floodwater management in rice, water pumped from aquifers could be reduced by about a quarter and methane emissions from rice fields could be cut down by about half without affecting grain yields, thereby promoting sustainable water management and greenhouse gas emission reduction during rice production in the Lower Mississippi Delta.

Pakistan’s Water Security Issue & Impacts of Floods

Water security is a crucial issue for Pakistan due to its heavy dependence on agriculture and limited water resources. The country has been facing multiple challenges in managing its water resources, including population growth, climate change, and water pollution. Among these challenges, floods pose a significant threat to Pakistan's water security, as they not only cause significant damage to infrastructure but also have long-term impacts on water availability and quality. This paper examines the impacts of floods on Pakistan's water security and highlights the key factors that contribute to the country's vulnerability to flooding. The paper reviews the existing literature on Pakistan's water resources and flood management strategies and identifies gaps in knowledge and policy. It also analyzes the socioeconomic impacts of floods on the local communities and the wider economy, emphasizing the role of water security in achieving sustainable development.The findings of this study suggest that Pakistan needs to adopt a holistic approach to water management that takes into account the complex interplay of factors that affect water security. This approach should involve the development of sustainable water use practices, the promotion of water conservation, and the implementation of effective flood management strategies. The study concludes that addressing Pakistan's water security challenges requires a coordinated effort by the government, civil society, and private sector, and calls for the development of a national water policy that prioritizes water security and sustainability.

Discharge Monitoring in Open-Channels: An Operational Rating Curve Management Tool.

An aspect correlated with climate change is certainly represented by the alternation of severe floods and relevant drought periods. Moreover, there is evidence that changes in climate and land cover are inducing changes in stream channel cross-sections, altering local channel capacity. A direct consequence of a significant change in the local channel capacity is that the relationship between the amount of water flowing at a given point in a river or stream (usually at gauging stations) and the corresponding stage in that section, known as a stage-discharge relationship or rating curve, is changed. The key messages deriving from the present work are: (a) the more frequent and extreme the floods become, the more rapid the changes in the stream channel cross-section become, (b) from an operational point of view, the collection and processing of field measurements of the stage and corresponding discharge at a given section in order to quickly and frequently update the rating curve becomes a priority. It is, therefore, necessary to define a control system for acquiring hydrological data capable of keeping river levels and discharges under control to support flood early warnings and water management. The proposed stage-discharge management system is used by the Civil Protection Service of the Marche Region (east-central Italy) for the monitoring of river runoff in the regional watersheds. The Civil Protection Service staff performs stage-discharge field measurements using water level sensors and recorders (e.g., staff gauges, submersible pressure transducers, ultrasound and radar sensors) and a current meter, acoustic doppler velocimeter, acoustic doppler current profilers, portable mobile radar profiler and salt dilution method equipment, respectively. Power functions are fitted to the stage-discharge field data. Furthermore, extrapolation is performed to cover the full range of flow measurements; in general, extrapolation is not an easy task because of sharp changes in the stream cross-section geometry for very high or very low stages. In the present work, we also focused attention on the application problems that occur in practice and the need for frequent updating.

FLOOD DAMAGE MITIGATION AND RESILIENCE IN BANGLADESH PERSPECTIVE

The northeastern part of Bangladesh is facing more diverse problems such as more frequent and severe floods, sea level rise, saltiness water, and loss of biodiversity due to poor management of flooding systems. This article investigates that about 55% ,60% & 50% area was sequentially inundated in A.D. 1988, A.D. 1998 and A.D.2007. These 3 floods were historically more horrible than any other catastrophic flood. In A.D. 2007 flooding made 9 million people homeless and roughly 1000 people died. However, due to institutional limitations, mismanagement and social conflicts, applications of the flood mitigation plan and water management approaches were not implemented. With every major flood in Bangladesh, water security and poverty situations are adversely affected. Heavy monsoon rain and water from upstream sources have triggered drainage levels occasionally considered the main causes of flood in Bangladesh. But this article explores that the main causes of flood of Bangladesh are lack of river beds mining, lack of stabilizing trees, dam, and lack of bank revetment both sides of the river. According to the field data, in Bangladesh there are only 35% of flood protected zone. On the contrary, there are 52% of flood unprotected area. This article analyzed flood hazard in Bangladesh and try to make nature-based solutions for mitigating this vulnerability.

Key Advances in Modelling Flood Water Management

Key Advances in Modelling Flood Water Management

Optimisation of urban-rural nature-based solutions for integrated catchment water management

Nature-based solutions (NBS) have co-benefits for water availability, water quality, and flood management. However, searching for optimal integrated urban-rural NBS planning to maximise co-benefits at a catchment scale is still limited by fragmented evaluation. This study develops an integrated urban-rural NBS planning optimisation framework based on the CatchWat-SD model, which is developed to simulate a multi-catchment integrated water cycle in the Norfolk region, UK. Three rural (runoff attenuation features, regenerative farming, floodplain) and two urban (urban green space, constructed wastewater wetlands) NBS interventions are integrated into the model at a range of implementation scales. A many-objective optimisation problem with seven water management objectives to account for flow, quality and cost indicators is formulated, and the NSGAII algorithm is adopted to search for optimal NBS portfolios. Results show that rural NBS have more significant impacts across the catchment, which increase with the scale of implementation. Integrated urban-rural NBS planning can improve water availability, water quality, and flood management simultaneously, though trade-offs exist between different objectives. Runoff attenuation features and floodplains provide the greatest benefits for water availability. Regenerative farming is most effective for water quality and flood management, though it decreases water availability by up to 15% because it retains more water in the soil. Phosphorus levels are best reduced by expansion of urban green space to decrease loading on combined sewer systems, though this trades off against water availability, flood, nitrogen and suspended solids. The proposed framework enables spatial prioritisation of NBS, which may ultimately guide multi-stakeholder decision-making, bridging the urban-rural divide in catchment water management.

A Review on the Numerical Studies on the Performance of Proton Exchange Membrane Fuel Cell (PEMFC) Flow Channel Designs for Automotive Applications

Climate change and the major threat it poses to the environment and human lives is the major challenge the world faces today. To overcome this challenge, it is recommended that future automobiles have zero carbon exhaust emissions. Even though battery electric vehicles reduce carbon emissions relative to combustion engines, a carbon footprint still remains in the overall ecosystem unless the battery is powered by renewable energy sources. The proton exchange membrane fuel cell (PEMFC) is an alternate source for automotive mobility which, similar to battery electric vehicles, has zero carbon emissions from its exhaust pipe. Moreover, the typical system level efficiency of a PEMFC is higher than an equivalent internal combustion powertrain. This review article covers the background history, working principles, challenges and applications of PEMFCs for automotive transportation and power generation in industries. Since the performance of a PEMFC is greatly influenced by the design of the anode and cathode flow channels, an in-depth review has been carried out on different types of flow channel designs. This review reveals the importance of flow channel design with respect to uniform gas (reactant) distribution, membrane proton conductivity, water flooding and thermal management. An exhaustive study has been carried out on different types of flow channels, such as parallel, serpentine, interdigitated and bio-inspired, with respect to their performance and applications.

“Half a flood’s no good”: flooding, viticulture, and hydrosocial terroir in a South Australian wine region

Floods generate both risks and benefits. In Langhorne Creek, South Australia, a historically-embedded system of shared floodwater management exists among farmers, who rely on semi-regular flood inundations as part of the region’s hydrosocial terroir – a dynamic conjunction of water, landscape, social relations and agricultural practice. Unruly floods coexist with a heavily regulated and precisely measured system of modern water management for viticultural irrigation across the region. Since the mid-twentieth century, groundwater extraction and new pipeline schemes have linked Langhorne Creek to the Murray Darling Basin water management system, which has displaced flooding as the primary source of irrigation water. The associated modernist shift towards the rationalization of water as a measurable resource has acted to sideline flood irrigation. Yet, floods maintain important viticultural, ecological and social roles in Langhorne Creek, adding to the flexibility and resilience of the region in response to water management challenges. The system involves technological and infrastructural components, such as flood gates and channels, but also relies upon the cooperation and coordination of community members. Local vignerons suggest that flood irrigation is environmentally as well as economically beneficial, rejuvenating riparian wetlands along watercourses. A more formal acknowledgement of the specific regional experiences of water management in a wine region like Langhorne Creek helps to fill a gap between emplaced and hydrosocial understandings of flood irrigation and broader assumptions about flooding as wasteful and inefficient.

Quantitative Assessment of Impact of Climate Change and Human Activities on Streamflow Changes Using an Improved Three-Parameter Monthly Water Balance Model

Understanding the impact of climate change and human activities on the hydrological cycle of any watershed can provide a scientific basis for regional water resource planning, flood management, and disaster mitigation. An improved three-parameter hydrological model (CM) based on monthly water balance using an exponential equation to depict the distribution of groundwater storage capacity was developed and evaluated. The model uses Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) rainfall data as input, with the Zhejiang Province as the case application, and the effects of climate change and human activities on streamflow changes were assessed by separating environmental variables in this study. The results indicate that APHRODITE data has excellent monthly accuracy, with a mean correlation coefficient (CC) of more than 0.96 and an average absolute percentage bias (Pbais) of less than 5%. The three models are relatively close in their ability to simulate high flows, but the CM simulated low flow is better than the other two models. Positive and negative Pbais phenomena occur in the CM model in each catchment, and absolute levels are regulated by 5%. Furthermore, the CM model’s average Nash efficiency coefficient (NSE) is greater than 0.9, indicating that it can correctly fulfill the water balance. The results are more consistent throughout multiple catchments in each watershed using Budyko-based and hydrological model technique to evaluate the influence of climate change and human activities on streamflow. Climate change dominated streamflow variations in 18 of the 21 catchments in Zhejiang Province, whereas human activities dominated the rest. The findings of the study will be used to influence the management, development, and usage of water resources in the watershed.

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.