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The process of “hysteresis” has widely attracted the attention of researchers and investigators due to its usage in many disciplines of science and engineering. Economics, physics, chemistry, electrical, mechanical, and petroleum engineering are some examples of disciplines that encounter hysteresis. However, the meaning of hysteresis varies from one field to another, and therefore, many definitions occur for this phenomenon depending on the area of interest. The “hysteresis” phenomenon in petroleum engineering has gained the attention of researchers and investigators lately, because of the role that plays in reservoir engineering and reservoir simulation. Hysteretic effects influence reservoir performance. Therefore, an accurate estimation of rock and fluid property curves has an essential role in evaluating hydrocarbon recovery processes. In this paper, a comprehensive review of research and growth on the hysteresis of wettability for its applications in petroleum engineering is reported. Also, theoretical and experimental investigations of hysteresis of wettability are compared and discussed in detail. The review highlights a range of concepts in existing models and experimental processes for wettability hysteresis. Furthermore, this paper tracks the current development of hysteresis and provides insight for future trends in the research. Finally, it reveals an outlook on the research challenges and weaknesses of hysteresis of wettability.

Currently, engineers are using numerical correlations to describe the flow of oil and gas through chokes. These numerical correlations are not 100% accurate, as indicated by other studies, so there is a need to find a better approach to describe and calculate the choke size. Artificial intelligence (AI) can be used for better results. In this study, AI was used to estimate the optimum choke size that is required to meet the desired flow rate. Four techniques are used in this study: artificial neural networks, fuzzy logic (FL), support vector machines, and functional networks. Results obtained using these techniques were compared. After researching each technique, FL was found to give the best predictions.

Thermal flooding is one of the most successful and widely used processes for heavy oil recovery. The memory-based fluid flow model is effective in characterizing reservoir heat transport mechanism, temperature profile, and predicting the performance of thermal recovery. Temperature has a substantial effect on the thermodynamic properties such as thermal conductivity of the formation. In addition, the influence of temperature on reservoir rock and fluid properties plays an important role in accurately predicting reservoir temperature distribution, oil displacement, and steam oil ratio. This paper presents a critical review and analyses to provide inclusive information on the state-of-the-art memory-based fluid flow modeling during the thermal displacement process. The review highlights the assumptions and limitations of the current models in the areas of thermal conductivity, temperature distribution, oil displacement, and steam oil ratio during the thermal flooding process in porous media. This paper also serves to provide an insight into future research opportunities to fill the knowledge gaps in the subject area by applying the memory concept and further improvement of the current and classical models for heavy oil recovery.

Hysteresis has a significant role in evaluating hydrocarbon recovery and better understanding fluid flow in porous media. In this paper, a comprehensive review of research on the hysteresis of capillary pressure ( P c ) and its applications in petroleum engineering are reported. Both theoretical and experimental investigations of hysteresis of P c is compared and discussed in detail. The review highlights a range of concepts in existing models and experimental processes for hysteresis of P c in porous media. Furthermore, this paper tracks the current development of hysteresis and provides insight into future research trends. This study also serves to provide an insight into future research opportunities to fill the research gaps on capillary pressure in the system of porous media.

The science of Acoustics deals with the propagation of mechanical waves in the three phases of materials, solids, liquids, and gases. In exploration and reservoir engineering, acoustic wave velocities play an essential role in reservoir description. The primary challenge in the initial evaluation and characterization of reservoirs is related to the understanding of its geology, petrophysics, and geomechanics. Therefore, an accurate estimation of acoustic wave velocities and rock porosity is essential for better reservoir description and performance as well as a better forecast of seismic properties. In this reseach, the primary objective is to analyze the texture, mineralogy, porosity and permeability data of outcrop carbonate rock samples to study the impact of confining pressure on wave velocities. Furthermore, an empirical correlation is proposed for relating porosity with acoustic properties. Ninety outcrops samples are collected from Dam Formation in Al-Lidam area in Eastern Province, Saudi Arabia to develop a correlation. The carbonate samples varies from mudstone to grainstone facies. The samples are collected, prepared, and tested for this experimental study based on API standards. Compressional and shear wave velocities of carbonate rocks are measured under dry and fully brine-saturated conditions for 5 to 25 MPa effective confining pressures at room temperature. Moreover, porosity and permeability are measured using three different techniques, viz., AP-608 Automated Porosimeter-Permeameter, Helium Porosimeter, and thin section technique. Finally, the results are compared with those from other studies related to the same area. A state-of-the-art review is presented on seismic properties, relationship with porosity and acoustics in addition to the current trend and the future challenges in the area. The laboratory investigations for this study reveals that Al-Lidam area has different types of facies. The results also show that both compressional and shear wave velocities increase as the confining pressure on the dry samples increase. However, the compressional wave velocities increased and the shear wave velocities decreased with confining pressure under fully saturated conditions. A new correlation is presented for carbonate rocks to predict porosity from acoustic wave velocities. This study will help in improving the exploration efforts as well as give a better explanation for reservoir characterization, facies recognition, geophysical interpretation, and engineering calculations. This attempt will open a new research area for engineers and scientists to study the effect of variation in different properties on wave velocities.

Reservoir entropy generation has a significant role in production cycles of a hydrocarbon reservoir. During production, entropy generation characterizes the irreversible fluid energy losses. This paper aims to develop a new production strategy that minimizes the entropy production to improve operational efficiencies. The second law of thermodynamics is used to calculate entropy generation in a porous medium during hydrocarbon production. The model considers different sections of a production system, including the reservoir, near-wellbore, and wellbore regions. The proposed model is an extension of the Civan model. The introduced model considers the near wellbore region as a separate zone, which allows flexibility in modelling skin effects near the wellbore. In addition, a new performance criterion, called the coefficient of performance (COP). This COP integrates the recovery factor with entropy generation and provides a quantitative measure to optimize the reservoir production. The model is used to conduct a parametric sensitivity analysis including effects of fluid and rock parameters such as permeability, porosity, viscosity, skin factor, and temperature on the total entropy production. The COP is used to optimize operating conditions of the reservoir such as production rates and bottomhole pressure. It was found that permeability and the bottom hole pressure have the most impact on the total entropy production. This article will present new approaches and findings to maximize the recovery efficiency by minimizing entropy generation of fluid transport processes in a hydrocarbon reservoir.

The term "hysteresis" has been used for a long time. The researchers were paying attention because of its wider usages in many disciplines of science and engineering. However, the concept of hysteresis may differ from one discipline to other depending on parameters of interest. The effect of hysteretic on reservoir performance can be either negative or positive. Therefore, evaluation of hydrocarbon recovery techniques will depend on the accurate estimation of the rock and fluid properties. Many researchers believe that hysteresis behaviour in rock properties is related to the concept of unrecovered hydrocarbon. Numerous experimental and mathematical studies are offered to understand the hysteresis of rock properties. However, researchers paid more attention to the relative permeability hysteresis because of its important contributions on mobility ratio toward the oil recovery. The purpose of this paper is to extensively review, discuss and analyze the fundamentals of experimental processes and mathematical models of relative permeability hysteresis. In addition, the importance of relative permeability hysteresis in reservoir engineering is highlighted. In the literature, no attempt has been made to refer and review the relative permeability hysteresis despite numerous published papers. This paper considers offering a comprehensive critical review and analysis of hysteresis that related to petroleum engineering. A systematic approach to literature survey is followed to offer a future research guideline in the area. A critical analysis is offered on theoretical and empirical models for relative permeability hysteresis, the types of relative permeability hysteresis, factors affecting relative permeability hysteresis and rock types that are used in the experimental techniques to estimate the hysteresis. This paper tracks the current development on hysteresis and provides insight into future trends on the application of this phenomenon. The overall results show some missing concepts in existing models and experimental processes for the hysteresis. The finding also shows that for a better understanding of multiphase flow in porous media, it is essential to study the relative permeability hysteresis. Finally, this paper offers some recommendations for missing aspect and future research guidelines. The importance of relative permeability hysteresis in fluid flow through porous media is rebuilt in describing each of the flowing phases. In addition, this study will help in understanding better reservoir performance as well as reservoir description.

Reservoir properties (e.g., porosity, permeability, surface tension, viscosity, fluid saturation, wettability, reservoir thickness, pressure, and temperature) are the function of time. Time variation of rock-fluid properties in a reservoir can be defined as memory concept in the field of petroleum engineering. Introducing memory formalism in reservoir simulation allows to account the time-varying nature of rock-fluid properties and enables reservoir simulator to provide more accurate reservoir flow forecast. The key purpose of this paper is to summarize the details for developing a memory formalism-based reservoir simulator. Within the context of the study, the key concept of memory formalism and fractional calculus are precisely explained. A complete roadmap in preparing a memory formalism-based reservoir simulator is shown with example and application.

The mathematical approach is the most commonly used approach in reservoir simulation. The classical mathematical approach considers numerous impractical assumptions leading toward the development of unrealistic reservoir simulator. In contrast, recently developed engineering approach is much promising as it has numerous advantages, such as – scope of bypassing the formulation of partial differential equations and discretization of partial differential equations, the ability to avoid rigorous and complex mathematics, and capability of realistic representation of reservoir behaviour through eliminating spurious assumptions. The present study outlines the route map for developing a reservoir simulator using an engineering approach. Major challenges encountered in reservoir simulation and the fundamentals of various available modelling approaches are addressed in this paper. The outlook for both classical mathematical approach and engineering approach are reviewed along with their strengths and weaknesses. Fluid flow equations are derived based on the proposed engineering approach. To do that, a set of non-linear algebraic flow equations in the time integral form is developed using the mass balance equation, an equation of state, and a constitutive equation without going through the formulation of partial differential equations and discretization step. The time integral is then approximated to obtain the non-linear algebraic flow equations for all the gridblocks of the reservoir. The significance of the engineering approach for describing the accurate fluid flow through porous media is compared to the to conventional mathematical approach. The engineering approach provides the same fluid flow equations as the classical mathematical approach for both the radial cylindrical and cartesian coordinate system but, without going through the formulation of partial differential equations and discretization step. Much simpler ordinary differential equation solvers, e.g., Runge-Kutta method or Euler method can be used in the engineering approach to obtain the solution, whereas the classical mathematical approach does not have this advantage. Both the classical mathematical approach and the engineering approach treat the initial conditions in the same way. If classical mathematical approach uses second-order approximation then the same accuracy is obtained for both approaches in treating the boundary conditions. The engineering approach provides more precise dealing to the constant pressure boundary condition for block-centred gridding system in case of using the first-order approximation. The engineering approach gives the justification of using the central difference approximation for second order space derivative in classical mathematical approach. Results show that the proposed engineering approach based fluid flow model provides better flow prediction than the conventional mathematical approach based flow model. The outcome of this study will help engineers and researchers to develop more transparent simulator instead of creating a black box where the natural chaotic behaviour of the underground reservoir will be more understandable.

Recently, experimental and mathematical studies helped researchers to investigate and understand the fundamentals of hysteresis behavior in rock properties. Porosity and permeability are the two of the most important rock properties that are used to characterize the ability to store and transport hydrocarbons in porous media. Hysteresis plays an essential role in porous media and depends on several physical and mechanical properties. In petroleum and geomechanics engineering, understanding hysteresis behavior of porosity and permeability is required for hydrocarbon production plan. Numerous mathematical and experimental studies have been conducted to understand the effect of hysteresis on rock properties, and how they can play a role in improving the productivity of well. Therefore, it is essential to study hysteresis of rock properties, especially porosity and permeability. This paper presents a comprehensive review and critical analysis of porosity and permeability hysteresis, experimental and mathematical studies. In this paper, an effort to bring together much of this information into one source is highlighted for a better understanding of reservoir performance and description. Moreover, this paper tracks the current development on hysteresis and gives some insight for future studies on the application of hysteresis on rock properties. This article offers an extensive review and critical analysis on different kinds of hysteresis phenomenon of permeability and porosity such as porosity-permeability vs. net stress hysteresis, and porosity-permeability vs. temperature hysteresis. The review also includes mathematical models that are developed to represent this phenomenon as well as procedures of the experimental works and the devices used in the experimental studies. The finding concludes with highlighting some missing concepts in existing models and experimental procedures for porosity and permeability hysteresis. In the literature, no attempt is made to refer and review the hysteresis despite numerous works have been accomplished. Based on this fact, this article considers one of a kind and it is the first attempt to provide a complete and comprehensive review of porosity and permeability hysteresis. This research will help in understanding the impact of a hysteresis effect in petroleum engineering, and the production strategies of hydrocarbons specifically in low-permeability reservoirs such as shale, tight sandstone, and tight carbonates.

This paper shows the importance of Artificial Intelligence (AI) techniques as a practical engineering tool for predicting and estimating the gas flow rate through chokes. Studying the single gas flow through wellhead chokes is vital to the oil industry, not only to ensure the accurate estimation of gas flow rate but also to keep equipments protected from damage due to high gas flow rate. It also has the potential to avoid sand problems. Many studies have investigated the predictability of gas flow through chokes. In this paper, we reviewed, evaluated and compared the predictive performance of the available choke correlations in literature with five AI techniques. 162 data points were used to develop five AI models for predicting the gas flow rate. The data were fed to the five AI techniques Artificial Neural Network (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Network (FN) and Decision Tree (DT) (ANN, FL, SVM, FN and DT) and the results were optimized for each technique. The new models were found to perform better than the correlation and give the lowest error, with a mean absolute percentage error of 0.83%. Because of these reduced errors, the proposed AI-based models can improve gas flow rate prediction through chokes. The results of this paper will provide a better alternative to predictive modeling of petroleum reservoir properties. It will also open windows of opportunity for researchers and engineers to explore advanced machine learning techniques such as hybrids and ensembles for continued improvement of petroleum exploration and production.