Field Of Petroleum Engineering Research Articles

State of the Art on Relative Permeability Hysteresis in Porous Media: Petroleum Engineering Application

This paper delivers an examination of relative permeability hysteresis in porous media in the field of petroleum engineering, encompassing mathematical modeling, experimental studies, and their practical implications. It explores two-phase and three-phase models, elucidating the generation of scanning curves and their applications in various porous materials. Building on the research of traditional relative permeability hysteresis models, we have incorporated literature on forward calculations of relative permeability based on digital rock core models. This offers a new perspective for studying the hysteresis effect in relative permeability. Additionally, it compiles insights from direct relative permeability and flow-through experiments, accentuating the methodologies and key findings. With a focus on enhanced oil recovery (EOR), carbon capture, utilization and sequestration (CCUS), and hydrogen storage applications, the paper identifies existing research voids and proposes avenues for future inquiry, laying the groundwork for advancing recovery techniques in oil and gas sectors.

Thermal Cycling Stability of Ti-Zr-Nb-Al Shape Memory Alloy

Shape memory alloys, as a novel class of intelligent materials, possess substantial application potential in the field of petroleum engineering at elevated temperatures. However, the complex downhole environment necessitates the alloy to endure alternating cycles of cold and heat, demanding both a high phase transformation temperature and excellent thermal cycling stability. This study focuses on a quaternary Ti-Zr-Nb-Al shape memory alloy, examining the thermal cycling stability of the Ti-20Zr-10Nb-xAl (x=1, 2, 3, 4 at%) alloys after subjecting them to 50 thermal cycles. Results indicate that the alloy composition, post 50 cycles, transitions from a single martensite α'' -phase to a duplex microstructure comprising α''-phase and β-phase. Changes in Al content did not significantly affect the phase composition of the alloy in its thermally cycled state. As Al content increases, both the tensile strength and shape memory effect of the alloy initially improve before declining. In terms of shape memory properties, the Ti-20Zr-10Nb-2Al alloy sample exhibits the most favorable thermal cycling stability, characterized by a tensile strength of 692 MPa, an elongation of 6%, a shape memory effect of 0.96% under 4% pre-strain, a shape memory recovery rate of 38%, and a Vickers microhardness of 381 HV.

Digital twinning of temperature fields for modular multilayer multiphase pipeline structures

The temperature field of oil and gas wells in the field of petroleum engineering presents a core problem and challenge in the digital twin framework due to its ultra-long-distance and highly variable structural characteristics. The varying wellbore cross-sectional structures with depth make it difficult to establish an effective and generalized analytical model for heat transfer. In this study, we propose, for the first time, a method to automate the construction of multi-layered and multi-component heat transfer models by using a general computational model based on non-steady-state single-phase structural modules. This method enables the automated generation of complex multi-layered and multi-component heat transfer models, thereby achieving the construction of a generalized model for temperature field characterization with varying wellbore cross-sectional structures over ultra-long distances. Utilizing this modeling approach, we validate the proposed method through case studies using actual wellbore temperature field data. The results demonstrate the lightweight and efficient computational analysis of temperature field information under non-steady-state conditions.

Q&A With Dennis Denney, JPT Technology Focus Creator

_ In 1997, JPT debuted a monthly feature that represented an unconventional approach in meeting SPE’s goal of disseminating technical information to its members. Soon titled “Technology Focus,” the feature brought together subject-matter experts (SMEs) in a range of important industry topics to review technical-paper abstracts gathered from the previous year of SPE meetings, as well as the Offshore Technology Conference. Its architect, engineer, and pilot was Technology Editor Dennis Denney, who would become a familiar presence to SPE members and staff alike over a 17-year career, although his industry roots extended to his college days. Dennis helped recruit SMEs for review service; sent them hundreds of abstracts and full papers (monthly, that is; the cumulative count of papers he handled is likely a six-digit figure); answered their questions and concerns with prompt, supportive guidance; and then, once papers had been selected, synopsized them for publication in the magazine with the longtime help of Assistant Technology Editor Karen Bybee. As this writer well knows, condensing a 10,000-word paper on, say, distributed quasi-Newton derivative-free optimization methods for field development optimization into a 1,500-word summary that captures the novelty and technical sophistication of its authors’ work can be a daunting task. Applying his own background as a petroleum engineer to methodically analyze and trim each chosen paper, Dennis did just that dozens of times a year, transforming these texts into svelte packages that included only one table or figure to deliver the highest possible quantity of quality to JPT readers. When Dennis retired in 2013, I initially split his eyebrow-raising workload with fellow Technology Editor Adam Wilson (now JPT’s Special Publications Editor). It was immediately clear from the way that reviewers spoke about Dennis, and his contributions to the magazine and SPE itself, that he was held in the same high regard outside of the organization as he was within it, a testament to the reputation he had earned while working with so many members and SMEs. It was entirely fitting that, for JPT’s 75th anniversary celebration, we caught up with Dennis to reflect on his achievements in the industry and with the groundbreaking Technology Focus feature he created. Dennis lives with his wife Linda in Rockwall, Texas—not too far from SPE headquarters in Dallas, but not too close, either!—enjoying his retirement and his family. (Note: For more on the development and history of the Technology Focus features, read the companion piece to this article, “Technology Focus Topics Reflect Industry Growth, Evolution Over 25+ Years.”) Why did you decide to go into the field of petroleum engineering? I worked several years as an engineering tech, testing gas wells, tracking well and reservoir pressures, and writing computer programs to analyze pressure data. The department manager encouraged me to finish my degree and become a petroleum engineer. So, after I received a scholarship from J. Harold Dunn (at age 28), my wife and I sold our house, packed our things into a U-Haul truck, and loaded two young kids into the car to move to Bryan/College Station to attend Texas A&M University.

Research on the Adjustment Strategy and Effect Evaluation of Oilfield in the Late Stage of Water Drive with Ultra High Water Cut

This article delves into the adjustment strategies for high water cut oil fields in the later stage of water flooding and their impact on oilfield performance. We conducted a series of experiments, including optimizing the layout of injection wells, comparing water quality improvement measures, comparing oilfield management and operation strategies, and applying efficient oil recovery technologies, to analyze and evaluate the effects of different strategies in detail. The experimental results indicate that the production and recovery rate of the oilfield show a stable increase over time, starting from an initial value of approximately 95 units. At the end of the 10th time cycle, this indicator accumulated to around 950 units. This indicates that artificial lifting technology has shown stable performance in improving oilfield performance. The results of this study emphasize the importance of adjusting strategies. By optimizing the layout of water injection wells, improving water quality, optimizing management and operation, and applying efficient oil recovery technologies, it is possible to significantly increase the production and recovery rate of oil fields in the later stage of water flooding with ultra-high water content, reduce the expansion of water shear zones, and achieve better economic benefits and sustainable development. These results are of great significance for practical applications in the field of petroleum engineering.

A deep learning-based approach for predicting oil production: A case study in the United States

The accuracy of oil production predictions is crucial in the field of petroleum engineering. However, due to the time series characteristics of oil production and the complex relationship among multiple influencing factors, traditional methods, and time series prediction techniques have limitations in fully extracting time series features and exploring the internal relationships between variables. Deep learning techniques possess unique advantages in solving nonlinear problems and time-series problems but require a significant amount of data and can only conduct short-term oil production predictions due to the nonlinear and chaotic nature of yield. Therefore, this work aims to establish a model that can overcome these limitations. A modified GRU (M-GRU) is proposed to extract time series features of variables and external economic information. Then, the autoregressive (AR) model is integrated into importing priori knowledge to enhance the model's capability in extracting time series information. In addition, feature mapping is used to improve convergence performance. Finally, A loss function that can dynamically adjust the weights is proposed, which can enhance the model's ability to fit from error-prone samples. By validating the proposed model using oil production data, it has been proven that the model can predict oil production accurately and outperform other models with a correlation coefficient reaching 0.99874. Further tests show that the model can provide accurate prediction results even with limited sample sizes and during coincidental events such as financial crises and COVID-19 epidemics, providing strong support for decision-making for reservoir engineers.

A Novel Prediction Model of the Drag Coefficient of Irregular Particles in Power-Law Fluids

The settlement drag coefficient of irregular particles in power-law fluids is a crucial parameter in the field of petroleum engineering. However, the irregular shape of the particle and the non-Newtonian rheological properties of the fluid make it challenging to predict the settlement drag coefficient. In this study, the spherical and irregular particle sedimentation processes in power-law fluids have been analyzed using a visual device and a high-speed camera system. A mechanical model dependent on the force balance of settlement particles was adopted to conduct a detailed statistical analysis of 114 spherical particle experimental results, and a prediction model of the drag coefficient of spherical particles in the power-law fluid was established with a mean relative error of 3.85%. On this basis, considering the influence of geometric shape on the law of particle sedimentation, a new irregular particle sedimentation resistance coefficient model in power-law fluid is established via the incorporation of the parameter circularity of 2D shape description c into the spherical particle sedimentation resistance coefficient predictive model. The parameters in the new irregular particle sedimentation resistance coefficient predictive model can be obtained via nonlinear data fitting of the 211 groups of irregular particles using experimental results in the power-law fluid. The model has high prediction accuracy for the drag coefficient of irregular particles in power-law fluid, with a mean relative error of 4.47, and expands the scope of engineering applications, which is of great significance for fracturing scheme design and wellbore cleaning.

Microfluidics for Carbonate Rock Improved Oil Recovery: Some Lessons from Fabrication, Operation, and Image Analysis

Summary After the successful implementation of lab-on-a-chip technology in chemical and biomedical applications, the field of petroleum engineering is currently developing microfluidics as a platform to complement traditional coreflooding experiments. Potentially, microfluidics can offer a fast, efficient, low-footprint, and low-cost method to screen many variables such as injection brine composition, reservoir temperature, and aging history for their effect on crude oil (CRO) release, calcite dissolution, and CO2 storage at the pore scale. Generally, visualization of the fluid displacements is possible, offering valuable mechanistic information. Besides the well-known glass- and silicon-based chips, microfluidic devices mimicking carbonate rock reservoirs are currently being developed as well. In this paper, we discuss different fabrication approaches for carbonate micromodels and their associated applications. One approach in which a glass micromodel is partially functionalized with calcite nanoparticles is discussed in more detail. Both the published works from several research groups and new experimental data from the authors are used to highlight the current capabilities, limitations, and possible extensions of microfluidics for studying carbonate rock systems. The presented insights and reflections should be very helpful in guiding the future designs of microfluidics and subsequent research studies.

Using in-situ strain measurements to evaluate the accuracy of stress estimation procedures from fracture injection/shut-in tests

Fracture injection/shut-in tests are commonly used to measure the state of stress in the subsurface. Injection creates a hydraulic fracture (or in some cases, opens a preexisting fracture), and then the pressure after shut-in is monitored to identify fracture closure. Different interpretation procedures have been proposed for estimating closure, and the procedures sometimes yield significantly different results. In this study, direct, in-situ strain measurements are used to observe fracture reopening and closure. The tests were performed as part of the EGS Collab project, a mesoscale project performed at 1.25 and 1.5 km depth at the Sanford Underground Research Facility. The tests were instrumented with the SIMFIP tool, a double-packer probe with a high-resolution three-dimensional borehole displacement sensor. The measurements provide a direct observation of the fracture closure signature, enabling a high-fidelity estimate of the fracture closure stress (ie, the normal stress on the fracture). In two of the four tests, injection created an opening mode fracture, and so the closure stress can be interpreted as the minimum principal stress. In the other two tests, injection probably opened preexisting natural fractures, and so the closure stress can be interpreted as the normal stress on the fractures. The strain measurements are compared against different proposed methods for estimating closure stress from pressure transients. The shut-in transients are analyzed with two techniques that are widely used in the field of petroleum engineering – the ‘tangent’ method and the ‘compliance’ method. In three of the four tests, the tangent method significantly underestimates the closure stress. The compliance method is reasonably accurate in all four tests. Closure stress is also interpreted using two other commonly-used methods – ‘first deviation from linearity’ and the method of (Hayashi and Haimson, 1991). In comparison with the SIMFIP data, these methods tend to overestimate the closure stress, evidently because they identify closure from early-time transient effects, such as near-wellbore tortuosity. In two of the tests, microseismic imaging provides an independent estimate of the size of the fracture created by injection. When combined with a simple mass balance calculation, the SIMFIP stress measurements yield predictions of fracture size that are reasonably consistent with the estimates from microseismic. The calculations imply an apparent fracture toughness 2-3x higher than typical laboratory-derived values.

Experimental study of the critical sand starting velocity of gas-water-sand flow in an inclined pipe

The purpose of this paper is to study the critical sand starting velocity and transformation law of flow pattern based on gas–water–sand three-phase flow in an inclined pipe. Firstly, the indoor simulation experiment system of gas–water–sand three-phase flow was used to test the conversion law of flow pattern based upon the different gas void fraction. Secondly, the influence of slug bubbles on sand migration was investigated according to distinctive hole deviation angles, gas void fraction and sand concentration. Finally, the critical sand starting velocity was tested based on dissimilar hole deviation angles, gas void fraction, sand concentration and sand particle size, and then the influence of the above-mentioned key parameters on the sand starting velocity was debated based on the force analysis of the sand particles. The experimental results illustrated that when the gas void fraction was less than 5%, it was bubbly flow. When it increased from 5% to 30%, the bubbly flow and slug flow coexisted. When it was between 30% and 50%, the slug flow and agitated flow coexisted. When it reached 50%, it was agitated flow. Providing that the hole deviation angle was 90°, the phenomenon of overall migration and wave-like migration on the surface of sand bed was observed. On the contrary, the phenomenon of rolling and jumping migration was recognized. The critical sand starting velocity was positively correlated with the hole deviation angle and sand particle size, but negatively associated with the gas void fraction and sand concentration. This research can provide a certain reference for sand-starting production in the field of petroleum engineering.

The Development and Application of EOS-based VT Phase Behavior Calculation Algorithms in Petroleum Industry

The use of equation of state (EOS)-based phase behavior calculations is widespread in the petroleum industry, including the calculation of oil and gas reserves, production forecasting, and optimization of enhanced oil recovery (EOR) plans, surface separator design, and pipe flow calculation. The most commonly used method for providing phase behavior information is PT phase-equilibrium-calculation algorithms, which have been extensively studied for decades. However, simulation and engineering design of these processes using VT phase-equilibrium- calculation algorithms is sometimes more convenient than using conventional PT algorithms and has distinct advantages. The VT algorithm has been continuously improved over the last decade to ensure calculation accuracy, robustness, and efficiency, and it has been gradually applied in the petroleum industry. This article provides an overview of research findings in the field of EOS-based VT phase behavior calculation algorithms and their applications in oil and gas engineering. The Helmholtz-free-energy minimization approach, the Gibbs-free-energy minimization approach, and the nested approach based on the PT algorithm are three typical VT algorithm approaches discussed. The petroleum industry’s main applications of phase equilibrium calculation using the VT algorithm are described. Furthermore, some existing problems are identified, and several prospects for the application of the VT algorithm in the petroleum engineering field are presented. A critical review of the current state of the VT algorithm process, we believe, will fill the gap by shedding light on the process’s flaws and limitations, future development areas, and new research topics.

Fractal Dimension of Digital 3D Rock Models with Different Pore Structures

The macroscopic physical properties of rocks are profoundly determined by their microstructure, and the research of accurately characterizing rock pore structure has been extensively carried out in the fields of petroleum engineering and geoscience. Fractal geometry is an effective means of quantitatively estimating the pore structure properties of porous media. In this study, the evolution law of the fractal dimension and the quantitative relationship between the fractal dimension and porosity were investigated based on the digital 3D rock models. First, three kinds of models with gradually changing pore structures, namely sedimentation, compaction, and cementation, were systematically reconstructed by the process-based approach. Then, the fractal dimensions of the skeleton, pore, and surface of the models were computed and analyzed. Finally, the relationships among the fractal dimension, porosity, and complexity were explored qualitatively. These works reveal the changing laws of three types of fractal dimensions for different pore structure models. The pore structure differences in sedimentation model can only be distinguished by the surface fractal dimension, while both pore and surface fractal dimensions are available parameters for characterizing different pore structures in compaction and cementation models. The quantitative relations between box-counting fractal dimension and porosity were established, which can be expressed by combining linear and logarithmic formulas. The comparison of fractal dimensions of compaction and cementation models proves that fractal dimensions can distinguish the subtle pore structure differences in digital 3D rock models. Understanding the evolution law between the fractal dimension and pore structure parameters provides more references for classifying and evaluating rock pore structure features using fractal dimensions.

New Model for Non-Spherical Particles Drag Coefficients in Non-Newtonian Fluid

The settlement drag coefficient of non-spherical particles (SDCNPs) is a crucial parameter in the field of petroleum engineering. Accurately predicting the SDCNPs in the fluid is essential to the selection and design of proppant and hydraulic design in the fracturing scheme. Although many models for anticipating the SDCNPs have been proposed, none of them can be adopted for non-Newtonian fluid (NNF) and Newtonian fluid (NF). In the investigation, the SDCNPs in NF and NNF are studied experimentally, and the anticipation mode of the settlement drag coefficient of spherical particles (SDCSPs) in different fluids (including Newton, Herschel-Bulkley and power law) is proposed. On this basis, the shape depiction parameter circularity is introduced to develop the SDCNPs. The results exhibit that the predicted values of the SDCNPs model perfectly align with the experimental values, and the average relative errors are 5.70%, 6.24% and 6.72%, respectively. The mode can accurately describe the settlement behavior of non-spherical particles (NSPs) and provide a basis for the application of NSPs in petroleum engineering.

Parametric Sensitivity Analysis of A Compressible Multiphase Flow Model in Porous Medium: Application to the Tsimiroro Madagascar Oil Reservoir

Modeling and numerical methods are two very important fields in physics and engineering sciences. In fluid mechanics, they allow us to study various complex problems and to make predictions of complex phenomena. However, in some cases like the field of petroleum engineering, many parameters like absolute permeability, relative permeability, porosity, capillary pressures, etc. are difficult to measure and / or estimate with certainty. The parametric sensitivity analysis of models provides an overview of the most influential parameters of a model and thus enables the model to be optimized. The study carried out in this work goes in this direction and has made it possible to identify the most influential parameters. The results obtained show that the most influential parameters of the model are the geometric characteristics of the reservoir, porosity and permeability, as well as the injection pressure in the wells.

MoO3-x quantum dots-based hydrogel with excellent light-triggered self-healing efficiency and pressure sensitive photoluminescence for accurate remote force measurement

Multi-responsive functional materials with simultaneous photothermal and photoluminescent properties have broad applicational prospects in the field of flexible electronics, devices and remote force detection and monitor. Here, a feasible method is developed by introducing MoO3-x quantum dots (MoO3-x QDs) and blue fluorescent carbon dots (B-CDs) into a strong hydrogel matrix to fabricate a novel composite hydrogel with concurrent photothermal and photoluminescent properties. Besides rendering the peculiar multifunctionalities, we found that the addition of photothermal MoO3-x QDs enhances the mechanical properties and self-healing properties of the composite hydrogel. The temperature of the MoO3-x-CDs-PVA (Polyvinyl Alcohol) hydrogel can rise by 30 °C within 1 min after 808 nm infrared laser irradiation and the self-healing efficiency could double after 40 s of irradiation. Moreover, there is a good linear relationship between the fluorescence intensity of the composite hydrogel and the external force, which can be used to monitor the force within a certain range. The monitoring range and sensitivity can be further improved by adjusting the infrared laser to for small force detection. Finally, the novel composite hydrogel is successfully applied to fracture monitoring in fracturing and force monitoring at different locations in the fluid model in the field of petroleum engineering.

Research trends in Petroleum Engineering Field of Study in 2016–2021 by The Lens data

This article discusses the major trends in Petroleum Engineering research in 2016–2021 based on a bibliometric analysis of metadata of articles indexed by The Lens platform. A comparative analysis of trends in the topics related to Petroleum Engineering is conducted. Major institutes, countries, and funding foundations involved in petroleum engineering research are identified. The leading role of Chinese institutes and foundations in undertaking this research is shown. Links are established between research areas in Petroleum Engineering, Geology and Ecology. Examples of highly cited articles reflecting the main features of publication trends in the field of Petroleum Engineering are given. A cluster analysis of 24,673 titles of articles on the subject of Petroleum Engineering is done, and the names of publications that most reflect the subject matter of each of the 10 identified clusters are presented. A growing interest in the topic of natural gas hydrates over the past four years is noted.

A Comparative Study on Stance Adverbs in Abstracts of Doctoral Dissertations by Chinese and Americans — A Case Study in Petroleum Engineering

Stance adverbs are one of the main means to express the author's attitude and views on proposition information. This study bases on self-built corpus, taking the English abstracts of Chinese and American doctoral dissertations in the field of petroleum engineering as the corpus and analyzing the characteristics of stance adverbs used by Chinese and their American counterparts. The results show that: 1) there is no statistically significant difference in the overall frequency of stance adverbs between Chinese and American doctors, and both of them show a tendency of "epistemic stance adverbs > attitude stance adverbs > style-of-speaking stance adverbs"; 2) There is no significant difference in the frequency of using epistemic stance adverbs between Chinese and American doctors, but Chinese doctors significantly use more boosters, a subcategory of epistemic stance adverbs, showing the rigid traces of English writing style. Chinese doctors significantly use certain hedges, the other subcategory of stance adverbs; 3) There was no statistically significant difference in the frequency of using attitude stance adverbs between Chinese and American doctors, but Chinese doctors use more attitude stance adverbs to express affect than evaluation; 4) There is no significant difference in the frequency of style-of-speaking stance adverbs between them, and the fact that the use of this kind of stance adverbs is used least may be affected by the stylistic characteristics of the English abstract.

Well logging prediction and uncertainty analysis based on recurrent neural network with attention mechanism and Bayesian theory

Deep learning technology can fit the nonlinear relations between different logging sequences. It solves the prediction problems that cannot be effectively disposed by traditional physical or empirical models. However, these deep learning models lack uncertainty analysis, which affects the popularity of logging prediction models in the petroleum engineering application. In this study, we investigate the nonlinear well logging prediction and uncertainty analysis methods based on recurrent neural network (RNN) with attention mechanism and Bayesian theory. A codec structure model based on gated recurrent unit (GRU) neural network and attention mechanism is established for data prediction. Integrating Bayesian theory into GRU neural network, a GRU Bayesian framework is presented to capture model uncertainty and data uncertainty. The importance of different logging sequences to the predicted goal at the same depth and a certain depth range is considered by using the attention mechanism, which improves the prediction accuracy and reduces the uncertainty of the prediction. Compressional waves sonic log (DTC) data of carbonate reservoir is predicted by using the existing logging attributes (density, spontaneous potential, natural gamma ray and deep investigate double lateral resistivity). Compared with the traditional RNN models, the accuracy of the constructed model has increased by 7.95% ( R 2 = 93.07%) and the error decreased by 1.7166% ( RMSE = 2.9261%) in the field data. More importantly, the proposed method can quantitatively analyze the uncertainties of the predicted results, which effectively heightens the application of the logging prediction model in the petroleum engineering field. • This study highlights the importance of uncertainty in the deep learning models of petroleum engineering field, which focus on nonlinear logging data prediction and quantitative analysis of the uncertainties. • A_GRU_Bayes model for predicting logging data is developed in this study. It can provide fast and effective high-quality data for further geological research and engineering application. • An uncertainty method to simultaneously capture model uncertainty and data uncertainty is provided. The uncertainty analysis can improve the model application in the field of petroleum engineering. • The introduction of multi-stage attention mechanism method effectively improves data quality. It enhances the accuracy of nonlinear logging data prediction and reduces the uncertainties of the predicted results.

Theoretical study of micropolar fluid flow in porous media

In this paper, a mathematical model of Hele-Shaw flow was developed on the basis of the field equation of micropolar fluid. The motion equation of micropolar fluid was extended to flow in porous media, contributing to the mathematical model of the unsteady radial flow of micropolar fluid in an infinite reservoir. The relations between flow velocity, pressure gradient and flow rate were obtained by solving the mathematical model under fixed production internal boundary and fixed-pressure external boundary conditions. In addition, the effect of the physical properties of micropolar fluid on its flow was analyzed. The results indicated a significant dependence between the apparent permeability and physical properties of micropolar fluid, which clearly deviated from the Newtonian fluid. The results showed that, as the ratio of rotational viscous force to Newtonian viscous force in the micropolar parameter and the characteristic length of the micropolar metamaterial increase, the non-Newtonian characteristics of the fluid become gradually more significant. The non- Newtonian behavior of micropolar fluid consequently becomes unneglected, leading to a decreasing apparent permeability. Compared with a Newtonian fluid, a micropolar fluid causes obvious flow resistance, resulting in larger energy consumption and lower flow rate. This study can provide an academic reference for nonlinear rheology and the flow of heterogeneous fluids in the fields of petroleum engineering and biofluid flow. Cited as: Zhu, W. Theoretical study of micropolar fluid flow in porous media. Advances in Geo-Energy Research, 2021, 5(4): 465-472, doi: 10.46690/ager.2021.04.11

Optimization techniques for petroleum engineering: A brief review

ABSTRACT Optimization in the production of oil comprises various processes to measure, analyze, model, prioritize, and implementation to enhance productivity of a field, reservoir, well, or surface. It is a practice to ensure recovery of developed reserves while maximizing returns. With the advancement of technologies associated with the field of petroleum engineering, there has always been an advent of an optimization technique. Albeit not abruptly but still with considerable consistency, conventional as well as nature inspired optimization techniques extend their roots in almost all complex problems of the world including petroleum engineering. In this article, we have reviewed the extensive use of optimization-based procedures and approaches in petroleum engineering that are being used to expand, develop, and generate petroleum fields with the appropriate designs and operations; reservoir development, planning and management.