New Insight in Enhanced Oil Recovery Process Analysis and Application

1. Introduction

With stable global economic development, the energy demand continues to rise, with oil consistently accounting for over 30% of primary energy consumption. The International Energy Agency (IEA) predicts that global daily oil demand will exceed 110 million barrels by 2040. However, the average reserves of newly discovered oilfields have significantly decreased compared to the 20th century, and traditional high-yield oilfields have generally entered the late stage of high water-cut development. Therefore, discovering new oilfields through advanced exploration technologies and substantially enhancing oil recovery from mature oilfields have become crucial approaches to ensuring global energy security. Efficient petroleum resource development constitutes a complex system engineering challenge, involving accurate oil prospecting, precise numerical modeling, water channeling identification, safe oil storage, and reservoir management.

This Special Issue, titled “New Insight in Enhanced Oil Recovery Process Analysis and Application”, aims to introduce the latest research advancements and field applications of methods for enhancing oil recovery rates. This Special Issue comprises 12 articles that cover a wide range of topics, including fundamental seepage mechanics fields such as relative permeability curves, multiphase flow models, and numerical simulation methods, as well as novel chemical flooding methods like heterogeneous composite flooding, foam flooding, and viscosity reducer flooding.

2. Overview of the Published Articles

As global oil and gas exploration progresses, the probability of discovering large, high-grade oil reservoirs has significantly declined, meaning that low-resistivity, low-porosity, and low-permeability resources have become the focus of future oil and gas exploration. Compared to conventional reservoirs, these types of reservoirs generally face challenges such as difficult reservoir identification and large fluid discrimination errors. Contribution 1 studied the effect of pyrite content on low-resistivity reservoirs by integrating well logging and petrophysical data. The authors of this study established a density–volume model for low-resistivity reservoirs and formulated a saturation calculation method based on a parallel conductivity model, effectively achieving the accurate identification of such reservoirs, and their work has significant theoretical and practical value for enhancing the exploration efficiency of complex oil reservoirs.

Relative permeability reflects the true flow capacity and mutual influence of multiphase fluids such as oil, gas, and water in porous media, determining the water breakthrough time, water-cut rise pattern, and ultimate oil recovery of reservoir development. It is a core parameter in multiphase percolation throughout the entire lifecycle of oil and gas development. Researchers have conducted extensive studies in this area [1,2]; however, the impact of displacement pressure gradients has rarely been considered. Contribution 2 analyzed the variation characteristics of oil–water relative permeability curves under different displacement pressure gradients through experimental testing and found that, as the displacement pressure gradient increases, the two-phase co-flow interval widens, and the water phase relative permeability increases. On this basis, they fitted the parameters of the Willhite model, revised the relative permeability curve model, and applied it to reservoir numerical simulations to better predict reservoir development dynamics and remaining oil distribution.

Low-permeability reservoirs, as the main type of unconventional oil resources, have become the key to ensuring energy security [3]. These reservoirs suffer from poor pore connectivity and complex distributions of microscopic remaining oil. Contribution 3 considered dissolved gas release, tested three-phase relative permeability curves, established a three-phase percolation simulation method, and combined it with displacement experiments to demonstrate that low-permeability cores experience more severe degassing phenomena and that water injection strategies and cycles significantly affect development outcomes.

China possesses substantial heavy oil reserves, but traditional thermal recovery methods generally exhibit low oil recovery rates and high carbon emissions. Chemical composite cold recovery techniques can substantially enhance crude oil recovery rates for heavy oil reservoirs. During the chemical composite cold recovery process, viscosity reducers emulsify with crude oil to form thermodynamically unstable emulsions [4,5], whose rheological properties and percolation mechanisms are complex, posing significant challenges for reservoir numerical simulation characterization. Contribution 4 characterized the chemical composite cold recovery system as a continuous oil phase, dispersed oil phase, and continuous water phase. Based on a capillary bundle model, they introduced a resistance factor parameter to reflect the additional resistance caused by the interaction between the dispersed oil phase and pore throat structure, proposing a new three-phase relative permeability characterization model to describe the complex flow behavior of emulsion systems in porous media. Their research findings contribute to the development of physical and chemical percolation theories for heavy oil chemical composite cold recovery.

Foam flooding involves injecting surfactants with air, nitrogen, or carbon dioxide into reservoirs to form foam systems, which utilize their “oil-defoaming, water-stabilizing” properties to block high-permeability channels, reduce water flow channeling, and force displacing fluids to divert into low-permeability layers, thereby enhancing crude oil recovery rates [6,7]. Due to the complex interactions of multiple flooding media involved in foam flooding, traditional reservoir-scale or mesoscale experimental and simulation methods struggle to accurately predict its microscopic interactions. Therefore, Contribution 5 considered foam jetting and oil-weakening mechanisms to improve a pore-scale filling model-based microscopic foam flooding characterization model, achieving accurate predictions of various foam flooding stages in accordance with microfluidic experiments. Their research also indicates that, for heterogeneous tight reservoirs, foam flooding should focus more on the interfacial tension adjustment capacity rather than solely pursuing strong foams.

Heterogeneous composite flooding introduces viscoelastic soft solid particles into polymer/surfactant solutions to enhance water sweeping and oil displacing capabilities, substantially improving oil recovery rates [8,9,10]. This method has successfully found industrial applications in China’s Shengli Oilfield and other locations. Heterogeneous composite flooding breaks the traditional limitation of using only homogeneous liquid or gas phases as displacement fluids in oil and gas field development and overcomes development bottlenecks for post-polymer flooding reservoirs. Based on reservoir development dynamic characteristics, differentiated production and injection allocation on a well-by-well basis are crucial for ensuring the optimal performance of heterogeneous composite flooding. Factors such as pore volume, permeability, heterogeneity, remaining oil saturation, formation coefficient, and reservoir pressure all influence chemical flooding production and injection allocation; however, which factors are primary and which are secondary remain unclear. Therefore, Contribution 6 combined well group zoning, development field data statistics, and sensitivity analysis to determine the primary controlling factors for chemical agent concentration, injection rate, and production rate, providing references for the rational allocation of production and injection in heterogeneous composite flooding.

Reservoir numerical simulation methods solve discretized partial differential equation groups describing multiphase percolation and their auxiliary conditions, and thus, they can predict reservoir dynamics and optimize development plans, serving as an essential simulation tool for enhancing oil recovery rates [11,12,13]. Fractured ancient buried hill reservoirs pose significant challenges for reservoir numerical simulation due to their high density of natural fractures and complex geological structures. To address this issue, Contribution 7 established an embedded discrete fracture numerical simulation model that also considers the fine characterization of condensate gas layers and volatile oil layers, revealing the primary controlling factors for the development of ancient buried hill condensate oil reservoirs and providing valuable references for the exploration and development of such reservoirs.

Most of China’s oil reservoirs are of continental deposition origin, exhibiting strong heterogeneity and significant variations in multiphase fluid relative permeability along different directions. However, common reservoir numerical simulation software struggles to account for the anisotropy of relative permeability. Therefore, Contribution 8 developed a multiscale solution method for pressure and transport equations that considers the anisotropy of reservoir relative permeability. They employed an improved multiscale finite volume method (IMsFV) to overcome computational errors in coarse-scale grids, balancing numerical simulation accuracy and computational efficiency. Based on this, they studied the impact of permeability and relative permeability anisotropy on water flooding development performance, providing an effective simulation and prediction tool for the development of anisotropic reservoirs.

Loose sandstone reservoirs, due to their high porosity and permeability characteristics, commonly exhibit vertical percolation of oil and water phases under weak dynamic conditions, which existing reservoir numerical simulators struggle to accurately describe. Therefore, Contribution 9 revealed the influence of permeability, crude oil viscosity, and saturation on vertical oil–water percolation based on microscopic experiments and established a vertical percolation prediction criterion formula. They then constructed a multiscale numerical simulation method that considers vertical oil–water percolation, achieving accurate simulation predictions of vertical oil–water phase distributions in loose sandstone reservoirs.

Long-term water injection leads to the formation of ineffective water circulation pathways with low flow resistance in reservoirs [14,15]. This process triggers particle migration and enlarges pore-throat radii. Consequently, reservoir heterogeneity is further exacerbated. Such ineffective water flow results in significant waste of injected water. It also intensifies the injection–production contradiction in reservoirs. Ultimately, development efficiency is reduced, and the operational lifespan of oilfields is substantially shortened. Therefore, it is essential to accurately identify channeling paths through development monitoring and other testing methods. On this basis, petroleum engineers can effectively prevent and treat water channeling through deep profile control and differentiated production and injection allocation. Currently, common methods such as tracer testing and water absorption/production profile monitoring face the problems of high computational costs and low efficiency. Contribution 10 simplified complex reservoirs into connecting units between injection and production wells. They established a quantitative identification model for water channeling paths. Comprehensive evaluation indicators and grading standards were proposed for water channeling in offshore loose sandstone reservoirs. Accurate identification and prediction of channeling locations, directions, and intensities were achieved. This provides a foundation for effectively implementing water channeling control measures.

Pumping units are the core surface equipment for oil development. The electrical power diagrams serve as the core monitoring graphics that reflect their operational status and reservoir dynamics. However, practical reservoir development faces limitations such as the lack of electrical power diagrams under different operating conditions and difficulties in diagnosing variable torque pumping unit conditions. Contribution 11 proposed a feature recognition-based condition diagnosis model. This model performs feature analysis and extraction on electrical power diagrams under different operating conditions. It directly diagnoses variable torque pumping unit conditions. This enhances oilfields’ intelligent management level.

Oil and gas storage tanks play a critical role in the petroleum industry, primarily used for storing and transporting oil resources and buffering pressure fluctuations. However, accidental leaks from oil and gas storage tanks can pose significant safety risks, such as vapor cloud explosions. Contribution 12 established a novel computational technique specifically for determining vapor cloud explosion overpressures. This innovative approach is fundamentally built upon the SLAB-TNO model structure. They rigorously assessed associated losses across diverse environmental and operational scenarios. Key parameters evaluated included gas diffusion time, wind speed, lower flammability limit, and temperature variations. Consequently, this research provides essential references for upgrading oil and gas storage facility designs and operations.

3. Conclusions and Perspectives

Despite the accelerating global energy transition, oil resources will continue to be a key component of primary energy consumption, particularly in areas such as chemical feedstocks and aviation fuels, where it is difficult to substitute. Enhancing oil recovery is a vital approach for efficiently developing petroleum resources and ensuring national energy security. This Special Issue provides comprehensive insight into various aspects, including relative permeability, numerical simulation models, and chemical flooding methods. We hope this Special Issue can offer new insights for researchers working on methods to improve oil recovery. We also recognize that, as petroleum exploration and development shift towards low-grade reservoirs, the adaptability of existing enhanced oil recovery methods is insufficient. As such, interdisciplinary collaboration is necessary to achieve breakthroughs in critical theoretical bottlenecks. In fact, the revolution in enhanced oil recovery methods has just begun, requiring more efforts from researchers worldwide.