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In this paper, the current advances in chemical injection method of polymer flooding are reviewed. The ultimate goal of polymer flooding for EOR process is to improve tertiary oil recovery by increasing the overall oil driving efficiency as a result of the improvements in injected fluid’s viscosity and mobility ratio. However, it was found that there were some limitations of polymer flooding. Hence, this paper will be reviewing studies on combinations of polymer flooding with other chemical methods by various researchers. Polymer flooding and its combinations with other flooding methods discussed in this paper are: polymer, alkaline polymer (AP), micellar polymer (MP), nanoparticles injection with polymers (NP) and alkaline surfactant polymer (ASP). The working principle, resistance, effectiveness and field application of each flooding method are also reviewed and compared.

Hurricane Harvey (2017) resulted in unprecedented damage from flooding in the Houston–Galveston area of the U.S. Gulf Coast. The objective of this study was to better quantify the impacts of compound flooding and to assess the relative contributions of storm surge, pluvial (rainfall) and fluvial (riverine) flooding using Hurricane Harvey as a case study. Here we developed a comprehensive numerical modeling framework to simulate flood extents and levels during Hurricane Harvey using Delft3D Flexible Mesh and validated results against observed water levels, waves, winds, hydrographs and high water marks. Results show that pluvial flooding dominated from widespread heavy rainfall during Harvey, accounting for ~ 60–65% of flooding. Pluvial flooding occurred mostly in watersheds and floodplains in West and South Bays (≤ ~ 1.5 m), upper Galveston Bay (Trinity River Basin, 2–3 m) and Harris County (≤ ~ 2.5 m). River runoff led to local ~ 1–2 m flooding. Significant storm surge levels were simulated northwest of the main Bay (2–2.5 m) and Galveston Bay (1–2 m) and in several watersheds in West/East of Galveston Bay. Wave action caused flood depth and water levels to rise by about 0.3–0.5 m in nearshore areas. Maximum flooding extent developed around August 29, 2017, which compared well to FEMA flood depth data. Nonlinear effects of compound flooding are greater than the sum of individual components. Results from this large-scale coupled modeling analysis provide a useful basis for coastal risk management and hazard mitigation. Our integrated framework is general and can be readily applied to other coastal compound flooding analyses.

Prolonged water injection in conventional heavy oil reservoirs typically leads to high water cut and a substantial reduction in recovery rate. This study explores the synergistic effects of a composite flooding process, where associated gas-assisted surfactant-polymer (SP) flooding is enabled by prior gel conformance control, to enhance oil recovery in these reservoirs. Through high-temperature, high-pressure microscopic visualization experiments and heterogeneous core flooding tests, the oil displacement mechanisms and enhanced recovery effects of this composite system were systematically investigated. The results show that SP flooding, through viscosity enhancement and reduction in interfacial tension, achieves the highest microscopic oil displacement efficiency, with an oil recovery of 81% and a significant reduction in clustered residual oil to just 9%. Associated gas flooding improves oil mobility by reducing viscosity and promoting expansion through gas dissolution, resulting in a recovery efficiency of 62%, which outperforms traditional viscosity reducers (58%). Heterogeneous core flooding experiments demonstrate that a composite strategy involving gel plugging, associated gas assistance, and SP flooding increases recovery by 24% compared to water flooding. The system also exhibits excellent flow control and maintains a low water cut, confirming the promising potential of this gel-conformance-controlled, associated gas-assisted SP flooding strategy as an effective method for enhancing recovery in high-water-cut heavy oil reservoirs.

Gas channeling treatment is a huge challenge for oil displacement and CO2 sequestration in the practical CO2 flooding process. The foaming agents can be used in the gas flooding process, which presents good application potential for gas channeling blockage. However, high temperature can affect surfactant foaming properties. This work takes a high-temperature heterogenous sandstone oil reservoir as an example; the foaming performance of different surfactants was evaluated via foamability, thermal stability, crude oil tolerance ability, and dynamic blocking capacity. The profile control performance of the optimized foaming agent was investigated via dual-core gas flooding experiments. (1) The results show that QPJ-c featured good foaming stability, which made it present the largest foam comprehensive index, although its foaming volume was slightly lower than that of QPJ-b. Its foaming volume retention rate was 83.2%, and its half-life retention rate remained 88.9% after 30 days aging at a temperature of 110 °C. (2) The foam resistance factor increased from 7 to 17 when the core permeability increased from 2 mD to 20 mD. This indicated that the high-permeability zone could be preferentially blocked by foam during the foam injection. (3) The dual-core flooding experiments verified that the fractional flow of the high-permeability core severely decreased due to the blockage of foam. The incremental oil recovery of the low-permeability core was 27.1% when the permeability ratio was 5. It increased to 40% when the permeability ratio was increased to 10. (4) Our work indicates that temperature-resistant CO2 foam could be a good candidate for profile control during CO2 flooding in the target reservoir.

When river and coastal floods coincide, their impacts are often worse than when they occur in isolation; such floods are examples of 'compound events'. To better understand the impacts of these compound events, we require an improved understanding of the dependence between coastal and river flooding on a global scale. Therefore, in this letter, we: provide the first assessment and mapping of the dependence between observed high sea-levels and high river discharge for deltas and estuaries around the globe; and demonstrate how this dependence may influence the joint probability of floods exceeding both the design discharge and design sea-level. The research was carried out by analysing the statistical dependence between observed sea-levels (and skew surge) from the GESLA-2 dataset, and river discharge using gauged data from the Global Runoff Data Centre, for 187 combinations of stations across the globe. Dependence was assessed using Kendall's rank correlation coefficient (τ) and copula models. We find significant dependence for skew surge conditional on annual maximum discharge at 22% of the stations studied, and for discharge conditional on annual maximum skew surge at 36% of the stations studied. Allowing a time-lag between the two variables up to 5 days, we find significant dependence for skew surge conditional on annual maximum discharge at 56% of stations, and for discharge conditional on annual maximum skew surge at 54% of stations. Using copula models, we show that the joint exceedance probability of events in which both the design discharge and design sea-level are exceeded can be several magnitudes higher when the dependence is considered, compared to when independence is assumed. We discuss several implications, showing that flood risk assessments in these regions should correctly account for these joint exceedance probabilities.

Chemicals are a pivotal part of many operations for the oil and gas industry. The purpose of chemical application in the subsurface reservoir is to decrease the mobility ratio between the displaced fluid and the displacing one or to increase the capillary number. These have been the favorable mechanisms for Enhanced Oil Recovery (EOR). Recently, it became a mainstay with EOR researchers looking for effective and efficient materials that can be economically feasible and environmentally friendly. Therefore, when the development of chemicals reached a peak point by introducing nanosized materials, it was of wondrous interest in EOR. Unlike other sizes, nanoparticles display distinct physical and chemical properties that can be utilized for multiple applications. Therefore, vast amounts of nanoparticles were examined in terms of formulation, size effect, reservoir condition, viscosity, IFT, and wettability alteration. When a holistic understanding of nanoparticles is aimed, it is necessary to review the recent studies comprehensively. This paper reviews the most recently published papers for nanoparticles in oil in general, emphasizing EOR, where most of these publications are between the years 2018 and 2022. It covers a thorough comparison of using nanoparticles in different EOR techniques and the expected range of oil recovery improvements. Moreover, this paper highlights the gaps existing in the field-scale implementation of NPs in EOR and opens space for research and development. The findings of this review paper suggest that the selection of the best NPs type for an EOR application is critical to the reservoir rock properties and conditions, reservoir fluids type, EOR mechanism, chemicals type (surfactant/polymer/alkaline), chemicals concentration used in the flooding process, and NPs properties and concentration.

Pluvial (surface water) flooding is often the cause of significant flood damage in urban areas. However, pluvial flooding is often overlooked in catchments which are historically known for fluvial floods. In this study, we present a conceptual remote sensing based integrated approach to enhance current practice in the estimation of flood extent and damage and characterise the spatial distribution of pluvial and fluvial flooding. Cockermouth, a town which is highly prone to flooding, was selected as a study site. The flood event caused by named storm Desmond in 2015 (5-6/12/2015) was selected for this study. A high resolution digital elevation model (DEM) was produced from a composite digital surface model (DSM) and a digital terrain model (DTM) obtained from the Environment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D for the study site. Simulations were carried out with and without pluvial flooding. Calibrated models were then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas for different land use types. The number of residential properties affected by both fluvial and combined flooding was compared using a combination of modelled results and data collected from Unmanned Aircraft Systems (UAS). As far as the authors are aware, this is the first time that remote sensing data, hydrological modelling and flood damage data at a property level have been combined to differentiate between the extent of flooding and damage caused by fluvial and pluvial flooding in the same event. Results show that the contribution of pluvial flooding should not be ignored, even in a catchment where fluvial flooding is the major cause of the flood damages. Although the additional flood depths caused by the pluvial contribution were lower than the fluvial flood depths, the affected area is still significant. Pluvial flooding increased the overall number of affected properties by 25%. In addition, it increased the flood depths in a number of properties that were identified as being affected by fluvial flooding, in some cases by more than 50%. These findings show the importance of taking pluvial flooding into consideration in flood management practices. Further, most of the data used in this study was obtained via remote sensing methods, including UAS. This demonstrates the merit of developing a remote sensing based framework to enhance current practices in the estimation of both flood extent and damage.

The scenarios when heavy rainfall and high tides occur in succession or simultaneously can lead to compound flooding. Compound floods exhibit greater destructiveness than floods caused by one driver in coastal cities. Prediction for compound floods with real-time and high accuracy can contribute to mitigating the losses caused by floods. However, existing rapid forecasting studies neglect the compound impact of rainfall and tides in coastal floods. In this study, the information on rainfall and tides is utilized as input features to capture the drivers of compound flooding. To reduce the risk of overfitting, the light gradient boosting machine (LightGBM) is employed for feature selection. The one-dimensional convolutional neural network (CNN) is then trained on the reduced-dimensionality data. Hence, we construct LightGBM-CNN to predict flood distribution in coastal cities. The model is applied on Haidian Island, Hainan Province, China. The results indicate that incorporating rainfall and tides as input features significantly reduced the mean absolute error (MAE) from 0.179 to 0.044 and the root mean square error (RMSE) from 0.223 to 0.101, compared to using rainfall as input features. Compared to the CNN without feature selection using LightGBM, the performance of LightGBM-CNN has shown a significant improvement. The results suggest that the LightGBM-CNN offers a foundational reference for compound flood forecasting in coastal cities.

Stormwater infrastructure can manage precipitation‐driven flooding when there are no obstructions to draining. Coastal areas increasingly experience recurrent flooding due to elevated water levels from storms or tides, but the inundation of coastal stormwater infrastructure by elevated water levels has not been broadly assessed. We conservatively estimated stormwater infrastructure inundation in municipalities along the Atlantic United States coast by using areas of high‐tide flooding (HTF) on roads as a proxy. We also modeled stormwater infrastructure inundation in four North Carolina municipalities and measured infrastructure inundation in one of the modeled municipalities. Combining methodologies at different scales provides context and allows the scope of stormwater infrastructure inundation to be broadly estimated. We found 137 census‐designated urban areas along the Atlantic coast with road area impacted by HTF, with a median percent of total road area subject to HTF of 0.16% (IQR: 0.02%–0.53%). Based on 2010 census block data, the median number of people per urban area that live in census blocks with HTF on roads was 1,622 (IQR: 366–5,779). In total, we estimate that over 2 million people live in census blocks where HTF occurs on roadways along the US Atlantic coast. Modeling results and water level measurements indicated that extensive inundation of underground stormwater infrastructure likely occurs at water levels within the mean tidal range. These results suggest that stormwater infrastructure inundation along the US Atlantic coast is likely widespread, affects a large number of people, occurs frequently, and increases the occurrence of urban flooding. Plain Language Summary Urban areas are often drained by underground pipes that convey stormwater runoff downstream when it rains, but coastal urban areas can experience recurrent “high‐tide” flooding (HTF) that may block stormwater pipes from draining. We estimated where stormwater pipes may be influenced by recurrent flooding in urban areas along the Atlantic United States coast by finding where HTF occurs on roads. We also modeled the impacts of stormwater pipe inundation in four North Carolina municipalities and measured inundation in one of the modeled municipalities. Over 130 east coast urban areas had road area impacted by HTF and the number of people estimated to live in census blocks that had HTF on roads was more than 2 million. Modeling results and water level measurements in the four North Carolina municipalities indicated that stormwater pipes likely have reduced capacity to convey stormwater at water levels within the average tidal range. These results suggest that stormwater infrastructure inundation is common and increases the occurrence of urban flooding along the east coast of the United States. Key Points Proxy measurements suggest that inundation of coastal stormwater networks from high water levels is common along the US Atlantic coast Measurements and modeling in coastal North Carolina showed stormwater network inundation at water levels within mean tidal range Stormwater network inundation likely increases risk of overland flooding in coastal urban areas