Reservoir Flood Research Articles

Fast Expansion of Surface Water Extent in Coastal Chinese Mainland from the 1980s to 2020 Based on Remote Sensing Monitoring

High-resolution satellite imagery providing long-term, continuous information on surface water extent in highly developed regions is paramount for elucidating the spatiotemporal dynamics of water bodies. The landscape of water bodies is a key indicator of water quality and ecological services. In this study, we analyzed surface water dynamics, including rivers, lakes, and reservoirs, using Landsat images spanning from the 1980s to 2020, with a focus on the highly developed Coastal Chinese Mainland (CCM) region. Our objectives were to investigate the temporal and spatial variations in surface water area extent and landscape characteristics, to explore the driving forces behind these variations, to gain insights into the complex interactions between water bodies and evolving environmental conditions, and ultimately to support sustainable development in coastal regions. Our findings revealed that reservoirs constitute the largest proportion of surface water, while lakes occupy the smallest share. Notably, a trend of expansion in surface water extent in the CCM was observed, mainly from the construction of new reservoirs. These reservoirs primarily gained new areas from agricultural land and river floodplains in the early stages (1980s–2000), while a greater proportion of construction land was encroached upon by reservoirs in later periods (2001–2020). At the landscape level, a tendency toward fragmentation and complexity in surface water, particularly in reservoirs, was evident. Human interference, particularly urbanization, played a pivotal role in driving the expansion of water surfaces. While reservoir construction benefits water resource assurance, flood control, and prevention, it also poses eco-hydrological challenges, including water quality deterioration, reduced hydrological connectivity, and aquatic ecosystem degradation. The findings of this study provide essential data support for sustainable water resource development. These insights underscore the urgency and importance of integrated water resource management strategies, particularly in efforts aimed at conservation and restoration of natural water bodies and the scientific regulation of artificial water bodies. Balancing human development needs with the preservation of ecological integrity is crucial to facilitating a water resource management strategy that integrates climatic and socio-economic dimensions, ensuring sustainable water use and protection for future generations.

Mechanism of CO2 flooding in shale reservoirs - insights from nanofluids.

The development potential of CO2-enhanced shale oil recovery is significant, but shale reservoirs have developed nanoscale pores, often accompanied by fissures and micro/nanoscale fractures. This characteristic makes the micro-nanoscale CO2 flooding mechanism unclear. In this study, the minimum miscible pressure (MMP) of CO2 and n-octane was determined from a microscopic perspective using the nanofluidic method. Based on this, the displacement behavior of CO2 in three types of micro-nano networks was investigated, and the degree of inter-fracture matrix utilization was studied for the first time using visualization techniques. It was found that compared to immiscible flooding, the stronger the heterogeneity, the more pronounced the improvement in recovery efficiency by miscible flooding. In addition, transfer and diffusion in the nanofracture network system are intense, and the displacement process can be divided into three stages: pressure-driven flow, matrix-fracture co-production, and matrix oil production. This study applies a novel nanofluidic method to extend the lower limit of the microscopic visualization experimental pore scale to 30 nm, filling the gap in experimental research on shale microscale flow and contributing to the understanding of the mechanism of CO2-enhanced recovery in shale reservoirs. Additionally, it provides necessary references for microscopic flow simulation.

Cyclic regulation of self-induced hydraulic fracturing cracks to improve the flooding efficiency of low-permeability reservoirs

The article is devoted to the topical issue of optimizing flooding in the development of deposits using a reservoir pressure maintenance system. In conditions of low permeability and weak reservoir connectivity, when water is injected into the injection well, when the injection pressure exceeds the pressure of rock rupture, auto-fracturing cracks occur. In order to ensure the maximum coverage factor of the reservoir by flooding during the development of the field, it is necessary to initiate and maintain the optimal fracture geometry of the auto-fracturing. The aim of the work is to analyze the modes of cyclic regulation of injection into the reservoir to maintain the optimal size of man-made cracks during the development of the field. The article presents the results of hydrodynamic modeling of flooding options with varying injection and shutdown times of injection wells, taking into account the geomechanical patterns of the spread of man-made cracks in the formation. Based on the results of the calculations performed, based on the forecast characteristics of displacement and the rate of oil extraction, the optimal modes of cyclic reservoir flooding were determined. The work is of great commercial importance, which is confirmed by the positive effect in the form of additional oil production within the framework of pilot tests of the proposed scheme. Keywords: self-induced hydraulic fracture; low-permeability reservoir; waterflood; water injection system; horizontal well; bottom hole pressure; reservoir pressure; fracture half-length; periodic injection of water.

Flood monitoring and reservoir management in the transboundary Chenab River Basin using machine learning and remote sensing techniques

Flood monitoring and reservoir management in the transboundary Chenab River Basin using machine learning and remote sensing techniques

Application of F-HGAPSO Algorithm in Reservoir Flood Control Optimal Operation

Application of F-HGAPSO Algorithm in Reservoir Flood Control Optimal Operation

Research on optimal scheduling of minor and moderate floods for cascade reservoirs in the lower reaches of the jinsha river considering power generation

The comprehensive cascade reservoir system is extensively used for flood control and power generation. Traditional reservoir scheduling often treats these tasks as competing objectives, prioritizing flood control during the flood season and neglecting power generation benefits. This approach, primarily applied to large floods, leads to hydraulic resource wastage and power generation loss during minor and moderate floods. The lower Jinsha River cascade reservoirs have significant flood control storage capacity, allowing part of the capacity to be used for maintaining higher water levels without compromising safety under minor and moderate floods within a 20-year return period. This paper proposes an optimal scheduling model that considers both flood control and power generation tasks for the lower Jinsha River cascade reservoirs. The Multi-objective Particle Swarm Optimization (MOPSO) algorithm was used to find non-inferior solution sets. An evaluation index system was developed to select optimal solutions under different flood frequencies, using the Minimum Discriminant Information Principle and VIKOR model. The results indicate that the optimal scheduling scheme under 20-year, 10-year, and 5-year return period floods can enhance power generation by 1.64, 1.71, and 1.35 billion kWh, respectively, compared to conventional scheduling. This approach supports coordinated flood control and power generation scheduling, contributing to the high-quality development of the Yangtze River Economic Belt.

Investigation of oil-based CO2 foam EOR and carbon mitigation in a 2D visualization physical model: Effects of different injection strategies

CO2 flooding in low-permeability and tight oil reservoirs often encounters gas channeling, which affects oil recovery. To address this, oil-based CO2 foam development is explored using a two-dimensional visual physical model. The study includes three experimental setups: CO2 flooding followed by oil-based CO2 foam flooding, CO2 Huff-n-Puff (HnP) followed by oil-based CO2 foam HnP, and oil-based CO2 foam HnP followed by oil-based CO2 foam flooding. Findings reveal that using oil-based CO2 foam after CO2 development increases recovery factors by 15.62% and 35.86% for HnP and flooding, respectively, and significantly boosts CO2 storage. The CO2 storage is 1.96 times and 6.03 times higher than the initial one. After oil-based CO2 foam is used, the red area near the outlet of the visualization model becomes shallower, indicating a further decrease in residual oil saturation. The oil-based CO2 foam method reduces residual oil saturation and extends production duration while decreasing gas production rates. This approach effectively plugs gas channels, enhancing CO2 sweep efficiency, crude oil mobility, and recovery. The results provide innovative strategies for oilfield development, supporting carbon sequestration and offering substantial economic and environmental benefits.

An updated reference table for extreme flood hydrology methods at UK dams

There are several possible methods available for extreme flood estimation applicable for UK dams and reservoirs. New models continue to be released to calculate both rainfall and runoff. This paper provides a short summary of the methods that are currently recommended for use in reservoir flood studies, and the methods that have been recommended in the past. This is intended to help inform reservoir owners, panel engineers and hydrologists of current best practice and the extent of changes in methodology since historical flood studies were undertaken. A simplified approach for sensitivity testing of multiple methods is proposed.

A Deep Learning-Based Three-Stage Method for Spillway Blockage Detection in Reservoirs

Spillway blockage detection is crucial for flood prevention and disaster reduction in reservoirs. To address the challenge of detecting the spillway blockages under complex environmental conditions such as rain and fog, this study proposed a three-stage spillway blockage detection method based on deep learning. This method involved the removal of the rain and fog interference, the segmentation of the spillway boundary region, and blockage detection. First, a rain and fog interference removal algorithm based on the dark channel prior theory was developed. Next, an improved lightweight DeepLabv3+ semantic segmentation algorithm was adopted to segment the spillway region from the images. Finally, the improved YOLOv7 object detection algorithm was utilized to identify the blockage debris within a segmented spillway area. The experimental results indicated that the proposed method achieved an average precision of 80.32% under normal conditions and 77.77% under complex conditions, representing improvements of 9.93% and 6.65%, respectively, compared to traditional methods. This method significantly enhanced the detection and identification of blockages in complex environments and could provide effective support for intelligent reservoir flood control and disaster reduction.

Numerical simulation of the effect of downstream material on scouring-sediment profile of combined spillway-gate

ABSTRACT Overflow structures are among the most important hydraulic structures used for measuring flow, controlling floods in reservoirs, and regulating water levels in open channels. Alternative options, such as combined structures like spillway-gates, are preferred due to their compatibility with natural and ecological needs. This study investigates the impact of different soil gradations downstream on the scouring profile of combined spillway-gate structures. Scouring and sedimentation downstream of the spillway-gate were examined under various particle sizes of 0.0008, 0.001, and 0.0014 m, with a constant density in both free and submerged flow conditions using the FLOW-3D software. In this study, the k-ε, k-ω, LES, and RNG turbulence models were evaluated, and the RNG turbulence model was selected among that group. In free flow conditions, the highest sediment deposition occurred with the smallest particle diameter. For larger particle diameters, the void spaces between the particles reduce friction and increase the movement threshold, leading to increased scouring and decreased sediment height. In submerged flow conditions, the changes in scouring for different particle sizes were minor, with results being closely aligned. In submerged flow conditions, increasing the particle diameter resulted in a decrease in sediment deposition in the post-scouring area.

Fractal model for heterogeneous effective diffusion and its application in compositional simulations of CO2 flooding in tight reservoirs

Fractal model for heterogeneous effective diffusion and its application in compositional simulations of CO₂ flooding in tight reservoirs

The Investigation into Sand Production Under Supercritical Carbon Dioxide (SC-CO2) Flooding in Sandstone Reservoirs Using the Resolved CFD-DEM Method

The Investigation into Sand Production Under Supercritical Carbon Dioxide (SC-CO2) Flooding in Sandstone Reservoirs Using the Resolved CFD-DEM Method

A Microscopic Experimental Study on the Dominant Flow Channels of Water Flooding in Ultra-High Water Cut Reservoirs

The water drive reservoir in Shengli Oilfield has entered a stage of ultra-high water cut development, forming an advantageous flow channel for the water drive, resulting in the inefficient and ineffective circulation of injected water. Therefore, the distribution characteristics of water drive flow channels and their controlled residual oil in ultra-high water cut reservoirs are of great significance for treating water drive dominant flow channels and utilizing discontinuous residual oil. Through microscopic physical simulation of water flooding, color mixing recognition and image analysis technology were used to visualize the evolution characteristics of water flooding seepage channels and their changes during the control process. Research has shown that during the ultra-high water content period, the shrinkage of the water drive seepage channel forms a dominant seepage channel, forming a “seepage barrier” at the boundary of the dominant seepage channel, and dividing the affected area into the water drive dominant seepage zone and the seepage stagnation zone. The advantage of water flooding is that the oil displacement efficiency in the permeable zone is as high as 80.5%, and the remaining oil is highly dispersed. The water phase is almost a single-phase flow, revealing the reason for high water consumption in this stage. The remaining oil outside the affected area and within the stagnant flow zone accounts for 89.8% of the remaining oil, which has the potential to further improve oil recovery in the later stage of ultra-high water cut. For the first time, the redundancy index was proposed to quantitatively evaluate the control effect of liquid extraction and liquid flow direction on the dominant flow channels in water flooding. Experimental data showed that both liquid extraction and liquid flow direction can regulate the dominant flow channels in water flooding and improve oil recovery under certain conditions. Microscopic physical simulation experiments were conducted through the transformation of well network form in the later stage of ultra-high water content, which showed that the synergistic effect of liquid extraction and liquid flow direction can significantly improve the oil recovery effect, with an oil recovery rate of 68.02%, deepening the understanding of improving oil recovery rate in the later stage of ultra-high water content.

Microfluidic Study of Application of Nanosuspension with Aluminum Oxide Nanofibers to Enhance Oil Recovery Factor During Reservoir Flooding

The paper presents the results of a comparative microfluidic study of the oil displacement process from a microfluidic chip simulating rock. Suspensions of spherical nanoparticles of silicon oxide (22 nm) and aluminum oxide (11 nm), as well as aluminum oxide nanofibers (8.7 nm in diameter and with an aspect ratio of 58), were used as displacing liquids. The nanofibers represent a unique new-generation crystalline material with a high aspect ratio. This work presents the first consideration of the use of aluminum oxide nanofibers as an additive for enhanced oil recovery. The comparative analysis has demonstrated that the addition of nanofibers can markedly enhance the oil recovery factor relative to the addition of spherical nanoparticles, other things being equal. Thus, in particular, it was demonstrated that the addition of nanofibers into the system allows for the greatest enhancement of the oil recovery factor, reaching a value of 25%, whereas the addition of spherical nanoparticles results in a maximum increment of approximately 10%. This is due to the fact that nanofiber additives have a tenfold stronger effect on the viscosity of nanosuspensions compared to similar additives of spherical particles. Nanosuspensions of aluminum oxide nanofibers exhibit non-Newtonian behavior at low concentrations. This opens the possibility of their extensive use in enhanced oil recovery.

Evaluation and regulation methods for the utilization of Type-II oil reservoirs using ASP flooding

Abstract Existing methods for calculating oil reservoir utilization in chemical flooding rely on the instantaneous water absorption profile, which fails to provide an accurate description of the actual utilization conditions of the reservoir, making it imperative to find a method that accurately reflects the reservoir utilization. Type-II oil reservoirs often exhibit significant vertical heterogeneity. During chemical flooding, the impacts of high-permeability layer utilization, low-permeability layer utilization, and the simultaneous utilization of both layers on recovery are to be explored. Therefore, it is important to investigate the recovery requirements for different types of reservoirs. This study explores the solutions for improved reservoir utilization as well as the evaluation and regulation methods for the utilization of secondary oil reservoirs using the Alkaline-Surfactant-Polymer (ASP) flooding, which is of great significance for the adjustment of ASP flooding, injection, and production of secondary oil reservoirs.

The characteristics of steam chamber expanding and the EOR mechanisms of tridimensional steam flooding (TSF) in thick heavy oil reservoirs

Aiming at the shortcoming of conventional steam flooding (CSF), tridimensional steam flooding (TSF) was proposed to expand the limited steam chamber and to enhance the low oil recovery in thick heavy oil reservoirs. In this paper, based on mechanisms of thermal recovery, two 3D experimental models were designed to investigate the evolution of steam chambers and production performance. A new method was proposed to utilize inflection point temperature and remaining oil saturation to identify utilizable ranges, hot water zones, and steam chambers. Then, based on the parameters of the indoor experiments, three numerical models were built to further study advantages of TSF. The results show that: i) Compared to CSF, TSF possesses a plumper steam chamber, a higher steam quality and a more stable displacement front; ii) The oil recovery of TSF can reach 52.85%, while it is only 43.31% for CSF at the same time; iii) At the end of TSF, the volume of steam chamber, low oil saturation zone, low pressure zone, and low viscosity zone is 3.08 times, 3.31 times, 1.61 times, and 1.55 times, respectively, compared to CSF, which demonstrates that TSF is effective. As a result, TSF can effectively expand steam chamber and enhance oil recovery in thick heavy oil reservoirs.

Enhance oil recovery by carbonized water flooding in tight oil reservoirs

The low permeability of tight sandstone reservoirs limits the application of water flooding to enhance oil recovery. Due to the properties of CO2, people improve crude oil recovery by carbonizing water flooding. However, many studies have not prioritized determining the concentration of carbonated water before comparing the recovery rates of carbonated water flooding and pure water flooding after water flooding. This article takes the Chang 6 oil reservoir as the research object, and uses a combination of nuclear magnetic resonance testing and displacement experiments to conduct experiments on optimizing the concentration of carbonated water. Based on this, experiments on water flooding and carbon water flooding after water flooding to improve crude oil recovery are conducted to compare and analyze the oil enhancement potential of carbonated water flooding. The experimental results show that the physical properties, pore throat structure and seepage capacity of sandstone samples of type I, II and III decrease in turn. With the increase of carbonated water concentration, the expansion coefficient, viscosity reduction rate, contact angle reduction rate and core permeability loss rate of crude oil increase. The damage rate of 0.4mmol/cm3 carbonated water solution (17.6 g CO2: 1 L water) to the core permeability is only 0.98%, which is the optimal experimental concentration. During the water flooding process, crude oil in pores of different scales in Type I rock cores is utilized, and the degree of utilization in large pores is relatively high. Continuing to use carbonated water to drive oil in the rock cores after water flooding increased the recovery rate of crude oil by 15.24%; The degree of crude oil utilization in small pores of Tpye II core after carbonization and water flooding increased by 29.4%, and the final recovery rate of crude oil increased by 11.35% compared to the core after water flooding; The physical properties of Tpye III core are poor, with a small proportion of large pores, resulting in a 9.04% increase in crude oil recovery rate. Compared with pure water flooding, the recovery rate and utilization degree of large and small pores in the three types of rock cores after carbonization water flooding have been improved to varying degrees. Among them, the utilization degree of crude oil in large pores is the most significant, which increases the recovery rate of crude oil in the rock core after displacement. This study can provide a theoretical basis for improving crude oil recovery by carbonizing water flooding.

The Effect of Dam Break Speed on Flood Evolution in a Downstream Reservoir of a Cascade Reservoir System

The dam break flood is one of the potential causes of catastrophic events in cascade hydropower hub groups. Investigating the movement patterns of dam break flooding among reservoir groups under different dam break speeds is crucial for flood prevention and emergency response. In this study, the evolution characteristics of dam break floods were investigated in a cascading reservoir system, focusing on different break speeds of the upstream dam. The results indicate that the dam break speed determines the concavity or convexity of the water level curve changes in the upstream reservoir. Accordingly, dam breaks are classified into three modes: instant dam break, fast dam break, and slow dam break. An approximate critical speed has been identified to differentiate between the fast dam break and slow dam break. Further investigation into the evolution patterns of dam break floods in downstream reservoirs under different break modes was conducted. Correspondingly, the flood peak discharge and peak arrival time of the dam break floods vary differently with break speed under different break modes. Finally, a theoretical analysis for the flood peak discharge at the dam site during gradual dam break at a certain speed was established, which is able to predict the over-dam flood peak discharge in fast and slow dam break modes. This study is based on a combination of laboratory flume experiments and three-dimensional numerical simulations. This study has theoretical significance for the reinforcement of public infrastructure safety and the prevention of natural disasters.

Including dynamic capacity impact in an improved model for optimal flood control operation in river-type reservoirs

Flood control operations in river-type reservoirs are significantly affected by both the dynamic reservoir capacity and flood propagation within the reservoir area. However, the traditional reservoir flood control optimal operation (RFCOO) model is usually based on the static capacity method, which may bring large errors in scheduling calculations for river-type reservoirs. To address this issue, an improved model, the reservoir dynamic capacity flood control optimal operation (RDCFCOO) model, that includes the influence of the dynamic reservoir capacity and flood propagation, was developed to improve the accuracy of flood regulation calculations in river-type reservoirs. This improved model includes a 1D unsteady flow simulation and a rederived objective function based on the maximum peak clipping criterion, and expresses the state transformation equations using the de Saint-Venant equations. Furthermore, a multi-core parallel DP (PDP) algorithm that incorporates reduction of state dimensionality (RSD) was developed to effectively derive optimal operation schemes. The improved model and algorithm developed herein were validated through an application to the Xiangjiaba Reservoir, China. The results show that: (1) By adding the item (qiw) to the objective function and substituting the de Saint-Venant equations for the water balance equation, the RDCFCOO model developed in this paper can account for the impact of dynamic capacity and flood propagation. As a result, it exhibits a more accurate and detailed flood control process that was closer to the actual conditions of river-type reservoirs compared to the RFCOO model; (2) By removing the invalid discrete state points from the search space and fully utilizing multi-core processors, the proposed PDP with RSD can significantly improve the computational efficiency of the DP in solving RDCFCOO problems. The improved model and algorithm can effectively improve the calculation accuracy of flood control optimal scheduling in river-type reservoirs and provide more information for decision-makers.

A prediction method of oil recovery for hot water chemical flooding in heavy oil reservoirs: Semi-analytical stream tube model

Abstract Chemical agents (polymer and surfactant) assisted hot water flooding is an effective means of enhancing oil recovery in heterogeneous and heavy oil reservoirs. The rapid prediction of oil recovery through hot water chemical flooding is very important. The stream tube model is a fast analytical method for predicting water flooding recovery, but it is not suitable for hot water chemical flooding. In this paper, a permeability distribution model for multi-stream tubes is established based on permeability variation coefficient using normal distribution function for reservoir heterogeneity, Using GOMPERTZ growth function model to characterize the changes in stream tube temperature, polymer viscosity, and surfactant concentration with injection volume, Using Brooks-Corey model to describe the influence of interfacial tension and temperature on the relative permeability curve. Finally, an analytical stream tube model for hot water chemical flooding of heavy oil reservoirs was established. The time discrete method is used to solve the model, then the graphs of the relationship between oil recovery and water cut are obtained. Compared with numerical simulation methods, the prediction error of oil recovery is less than 2%, and the calculation time is reduced by 89%. This model has been successfully applied to X oilfield. Based on historical fitting, it is predicted that hot water chemical flooding can enhance oil recovery by 6.3% compared to water flooding. This paper provides a fast calculation method for predicting and evaluating the effectiveness of hot water chemical flooding in heavy oil reservoirs.