Enhanced Oil Recovery Research Articles

Optimization of Gas Huff-n-Puff for Enhanced Oil Recovery in Shale Condensate Reservoirs in Jiyang Depressions, China

Optimization of Gas Huff-<i>n</i>-Puff for Enhanced Oil Recovery in Shale Condensate Reservoirs in Jiyang Depressions, China

Study on the Enhanced Oil Recovery Properties of the Pickering Emulsions for Harsh Reservoirs

Study on the Enhanced Oil Recovery Properties of the Pickering Emulsions for Harsh Reservoirs

Separate-Layer Injection Scheme Optimization Based on Integrated Injection Information With Artificial Neural Network and Residual Network

Abstract Separate-layer injection technology is a highly significant approach for enhancing oil recovery in the later stages of oilfield production. Both separate-layer and general injection information are crucial parameters in multi-layer oilfield injection systems. However, the significance of general injection information is usually overlooked during the optimization process of separate-layer injection. Moreover, conventional optimization schemes for separate-layer injection fail to meet the immediate and dynamic demands of well production. Consequently, a separate-layer injection optimization method based on artificial neural network and residual network (ANN-Res) model was proposed. Firstly, the primary controlling factors for production were identified through grey correlation analysis and ablation experiments. Then, a data-driven model was established with an artificial neural network (ANN), in which the residual block was utilized to incorporate general injection information, eventually forming an ANN-Res model that integrates separate-layer and general injection information. Finally, a workflow for separate-layer injection optimization was designed in association with the ANN-Res model. Analysis of primary controlling factor for production shows that the combination of separate-layer and general injection information for production prediction leads to redundancy. The results of injection–production prediction demonstrate that the ANN-Res model is significantly better than that of the ANN model which only inputs separate-layer or general injection information. Furthermore, the result of optimization proves the proposed method can be successfully applied to injection optimization, realizing the purpose of increasing oil production and decreasing water cuts, thereby improving oilfield development.

Research for the Enhanced Oil Recovery Mechanism of Heavy Oil After Composite Huff and Puff Assisted by Edge-Bottom Water Displacement

Abstract In the late stage of exploiting heavy oil reservoirs with edge-bottom water, we are faced with problems such as high crude oil viscosity, channeling of bottom water, and rapid rise in water cut. To clarify the synergistic effect of N2, CO2, N2 foam, and viscosity reducer in water control and oil increase, and solve the problem of edge-bottom water rushing into production wells, one-dimensional sand-pack huff and puff experiments were carried out. First, the N2 foam huff and puff experiment evaluated the effect of N2 foam on controlling bottom water. Then the viscosity reducer-assisted CO2 huff and puff experiment analyzed the synergistic viscosity reduction ability between the two to mobilize the remaining heavy oil. Next, the N2 foam–viscosity reducer–CO2 huff and puff experiment clarified the synergistic effect between the three. Finally, the N2 foam–viscosity reducer–CO2–N2 huff and puff experiment solved the problem of insufficient reservoir energy based on synergistic precipitation and oil increase. Experimental results show that N2 foam–viscosity reducer–CO2–N2 huff and puff is the optimal water control and oil increase solution. This solution can significantly reduce water production and increase oil production. In the one-dimensional sand-pack experiment, this technical solution reduced the water content by 68% and increased the recovery rate by 16.09%. The research results provide a reference for the development of exploitation technology schemes for similar edge-bottom water heavy oil reservoirs after entering high water cut.

New Insight of Nanosheet Enhanced Oil Recovery Modeling: Structural Disjoining Pressure and Profile Control Technique Simulation

This study presents a novel Enhanced Oil Recovery (EOR) method using Smart Black Nanocards (SLNs) to mitigate the environmental impact of conventional thermal recovery, especially under global warming. Unlike prior studies focusing on wettability alteration via adsorption, this research innovatively models ‘oil film detachment’ in a reservoir simulator to achieve wettability alteration. Using the CMG-STARS (2020) simulator, this study highlights SLNs’ superior performance over traditional chemical EOR and spherical nanoparticles by reducing residual oil saturation and shifting wettability toward water-wet conditions. The structural disjoining pressure (SDP) of SLNs reaches 20.99 × 103 Pa, 16.5 times higher than spherical particles with an 18.5 nm diameter. Supported by the Percus–Yevick (PY) theory, the numerical model achieves high accuracy in production history matching, with oil recovery and water cut fitting within precision error ranges of 0.02 and 0.05, respectively. This research advances chemical EOR technologies and offers an environmentally sustainable, efficient recovery strategy for low-permeability and heavy oil reservoirs, serving as a promising alternative to thermal methods.

Accurate modeling of crude oil and brine interfacial tension via robust machine learning approaches

Interfacial tension (IFT) between water and crude oil is a crucial variable that enhanced oil recovery (EOR) techniques can adjust to increase oil extraction from depleted fields. Most of the developed intelligent models in the literature are based on synthetic oil samples rather than real crude oil samples or brine total salinity rather than salinity of each salt type. Hence, this study applies various machine learning approaches, such as Convolutional Neural Networks (CNN), Adaptive Boosting (AdaBoost), Decision Trees (DT), Random Forest (RF), K-Nearest Neighbors (KNN), Ensemble Learning, Support Vector Machines (SVM), and Multi-Layer Perceptron Artificial Neural Networks (MLP-ANN) to develop advanced models for predicting the IFT between brine and crude oil considering real crude oil samples and taking the account of each salt type prevalent within the brine phase, which represent the realistic circumstances encountered in the oil reservoirs. These predictions are based on factors like the type and concentration of salt, the API of the crude oil, and the properties of the system (pressure and temperature) using previously published experimental data. A sensitivity analysis, incorporating a relevancy factor, is performed to highlight the influence of various input parameters on the IFT. Among these models, the Decision Tree is highlighted for its high accuracy and low training cost compared to ANN-based models, as evidenced by its emerged evaluation metrics (R-squared of 0.9796 and mean square error of 5e-4). It is noted that the AdaBoost model is the least accurate with an R2 of 0.6696. Furthermore, the sensitivity analysis indicates that the molecular weight of the salt has the smallest impact on the IFT, whereas temperature has the most significant effect. The developed smart model may be used to accurately estimate crude oil/brine IFT without needing tedious, time-consuming and expensive experimental workflows.

Innovative Pathways in Carbon Capture: Advancements and Strategic Approaches for Effective Carbon Capture, Utilization, and Storage

Due to carbon dioxide (CO2) levels, driven by our reliance on fossil fuels and deforestation, the challenge of global warming looms ever larger. The need to keep the global temperature rise below 1.5 °C has never been more pressing, pushing us toward innovative solutions. Enter carbon capture, utilization, and storage (CCUS) technologies, our frontline defense in the fight against climate change. Imagine a world where CO2, once a harbinger of environmental doom, is transformed into a tool for healing. This review takes you on a journey through the realm of CCUS, revealing how these technologies capture CO2 from the very sources of our industrial and power activities, repurpose it, and lock it away in geological vaults. We explore the various methods of capture—post-combustion, oxy-fuel combustion, and membrane separation—each with their own strengths and challenges. But it is not just about science; economics play a crucial role. The costs of capturing, transporting, and storing CO2 are substantial, but they come with the promise of a burgeoning market for CO2-derived products. We delve into these financial aspects and look at how captured CO2 can be repurposed for enhanced oil recovery, chemical manufacturing, and mineralization, turning waste into worth. We also examine the landscape of commercial-scale CCS projects, highlighting both global strides and regional nuances in their implementation. As we navigate through these advancements, we spotlight the potential of Artificial Intelligence (AI) to revolutionize CCUS processes, making them more efficient and cost-effective. In this sweeping review, we underscore the pivotal role of CCUS technologies in our global strategy to decarbonize and forge a path toward a sustainable future. Join us as we uncover how innovation, supportive policies, and public acceptance are paving the way for a cleaner, greener world.

Dynamics of HPAM flow and injectivity in sandstone porous media

Polymer flooding is a prominent chemical enhanced oil recovery (CEOR) method that involves the injection of polymer solution into the oil reservoirs to improve the sweep efficiency and maximize the ultimate oil recovery. Selecting an appropriate polymer type, molecular weight, and concentration is crucial for success of any polymer flooding project. This paper studies the flow behavior of HPAM-based EOR polymers with different molecular weights through porous media. Dynamic adsorption and injectivity tests were performed through 5 Darcies sandpacks using polymer solutions prepared with low (LM; 8–10 MDa) and high (HM; 20–25 MDa) molecular weight polymers. Polymer solutions with different target viscosity values of 7, 15 and 30 cP were flooded through sandpacks at the reservoir temperature of 80 ºC and pore pressure of 1000 psi. The results showed that HM solutions with different target viscosity have higher polymer retention through sandpacks compared to LM solutions. Furthermore, results of residual resistance factor (RRF) measurements were in line with dynamic adsorption tests results. That is, permeability reduction due to irreversible polymer retention was higher when HM polymer solutions were injected. Furthermore, the results showed that although the resistance factor (RF) and in-situ viscosity of HM and LM polymers are in the same range, however, shear thickening regime becomes pronounced in the case of HM polymer with higher target viscosity. Polymer relaxation time measurements, and consequently, Deborah number calculations were performed to describe the shear thickening behavior by polymers viscoelastic characteristics. Results demonstrate that occurrence of shear thickening regime is controlled by Deborah number which is a function of polymer molecular weight, polymer concentration and injection rate. These results shed light on the importance of the selection of optimal polymer molecular weight and concentration during the design of polymer flooding projects.

Sacrificing Surfactants to Improve Oil Recovery: A Fluid Density Functional Theory Study.

In the chemically enhanced oil recovery (CEOR) processes, heavy components in crude oil, such as asphaltenes, adhere to reservoir rocks, significantly impeding crude oil extraction. Surfactants are frequently utilized to improve oil recovery due to their ability to reduce interfacial tension (IFT) and modify surface wettability. Nevertheless, indiscriminate surfactant usage may result in resource wastage and hinder the attainment of optimal recovery outcomes. Therefore, it is urgent to accurately and efficiently screen out optimal surfactants suitable for different oil fields. This work employs fluid density functional theory (FDFT) to investigate the competitive adsorption mechanism of surfactants and asphaltenes on rock interfaces. We examined the impact of surfactants on asphaltene adsorption and determined the optimal surfactant concentration and chain length for differing reservoir electrical properties and asphaltene compositions. Furthermore, a comprehensive assessment of surfactants was conducted, considering both performance and economic factors. The findings contribute to a deeper comprehension of the displacement effect of surfactants on asphaltenes and offer scientific screening solutions for surfactants in oil recovery processes.

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 visualization of in‐situ emulsification during surfactant flooding

AbstractSurfactant plays a crucial role in the chemical enhanced oil recovery (cEOR) process, and in‐situ emulsification is regarded as one of the mechanisms for surfactant flooding. However, no direct evidences are available so far to show how emulsions are generated in porous media, and how emulsification is essential for cEOR. To address these issues, binary mixtures of several currently‐used sulfonate surfactants, SH5, SH6, and SHZ, were formulated with connate brine to displace crude oil in both 2D microfluidic chips and 3D glass beads porous media, as well as artificial cores. It was found that both “oil‐in‐water” (O/W) and “water‐in‐oil” (W/O) macroemulsions can be formed in‐situ inside the porous media, and they improve oil recovery mainly through breaking residual oil into small drops and improving mobility ratio, which can significantly reduce the residual oil saturation by up to 12.8% in 2D microchips. The in‐situ emulsification in 3D glass beads medium can get oil recovery factor up to 15% over water flooding. In‐situ formulation of microemulsion was also observed in microfluidic flow tests. Part of the oil phase is emulsified into microemulsions that are present in the middle phase, further mobilizing the oil trapped downstream, lowering residual oil saturation from 54.8% to 11.3% in 2D microchips, and enhancing oil recovery factor up to 25% in core flooding test. These findings advance insightful understanding of in‐situ emulsification during surfactant flooding process under simulated oil reservoir condition, offering real‐time evidence of how both macro‐ and micro‐emulsions formation help for cEOR.

Visualization and Simulation of Foam-Assisted Gas Drive Mechanism in Surface Karst Slit-Hole Type Reservoirs

Nitrogen injection technology has become an important production technology after water injection development in the karst fracture-vuggy reservoir in Tahe Oilfield. However, due to the influence of reservoir heterogeneity and the high mobility of gas fluid, nitrogen easily forms a dominant channel and gas channeling occurs, and the recovery effect time is short. Based on this, a visual surface karst model is designed and created to study nitrogen foam-assisted gas drive. The results show that after gas channeling occurs in the dominant channel of nitrogen flooding, foam injection-assisted gas flooding can improve oil recovery. In the longitudinal direction, foam-assisted gas drive mainly displaces the remaining oil because of gravity differentiation and the reduction of oil–water interfacial tension. In the horizontal direction, foam-assisted gas drive is mainly used to block the large pore cracks and dominant channels, promote the gas to turn into large tortuous and small cracks, and expand the swept efficiency of the gas. After forming the dominant channel, injecting 0.3 pv salt-sensitive foam with a gas–liquid ratio of 2:1 in the middle of the gas channel can improve the recovery rate of the model from 4% to about 25%, and the recovery rate can be increased by about 20%, which improves the effect of gas flushing and improves the development efficiency of the oil field at the same time.

Isolation and Characterization of Biosurfactant-Producing Bacteria for Enhancing Oil Recovery

Biosurfactants produced by bacteria possess remarkable emulsification properties for crude oil, significantly enhancing oil mobility and recovery rates. This study aimed to isolate and screen biosurfactant-producing bacteria for oil enhancing recovery. A total of 93 bacterial strains were isolated from marine sediments, with three high-yield biosurfactant-producing strains identified: Pseudomonas aeruginosa N33, Bacillus paralicheniformis Nian2, and Stenotrophomonas nematodicola T10. The fermentation conditions, such as pH, carbon source, nitrogen source, and C/N ratio, were optimized to maximize the yield and activity of biosurfactants. Further evaluations were performed to assess the stability of the bio-surfactant activity and its emulsification properties. The results indicated that all three strains produced biosurfactants that retained their oil displacement activity in the presence of Na+ and Mg2+, but showed a significant reduction in their activities in the presence of Ca2+. The biosurfactants maintained their original activity after treatment at 120 °C for 3 h. Additionally, the biosurfactants produced by all three strains demonstrated excellent oil emulsification capabilities. Static oil-washing and dynamic displacement experiments revealed static oil recovery rates of 28.1%, 23.4%, and 7.1%, respectively, for N33, Nian2, and T10, and dynamic oil displacement recovery rates of 95.0%, 74.1%, and 69.0%, respectively. This research provides valuable microbial resources for enhancing oil recovery via microorganisms and lays a foundation for practical application.

Review of Foam with Novel CO2-Soluble Surfactants for Improved Mobility Control in Tight Oil Reservoirs.

CO2-soluble surfactant foam systems have gained significant attention for their potential to enhance oil recovery, particularly in tight oil reservoirs where conventional water-soluble surfactants face challenges such as poor injectability and high reservoir sensitivity. This review provides a comprehensive explanation of the basic theory of CO2-soluble surfactant foam, its mechanism in enhanced oil recovery (EOR), and the classification and application of various CO2-soluble surfactants. The application of these surfactants in tight oil reservoirs, where low permeability and high water sensitivity limit traditional methods, is highlighted as a promising solution to improve CO2 mobility control and increase oil recovery. The mechanism of enhanced oil recovery by CO2-soluble surfactant foam involves the effective reduction of CO2 fluidity, the decrease in oil-gas flow ratio, and the stabilization of the displacement front. Foam plays a vital role in mitigating the issues of channeling and gravity separation often caused by simple CO2 injection. The reduction in gas fluidity can be attributed to the increase in apparent viscosity and trapped gas fraction. Future research should prioritize the development of more efficient and environmentally friendly CO2-soluble surfactants. It is essential to further explore the advantages and challenges associated with their practical applications in order to maximize their potential impact.

High performance emulsifier magnetic Janus nanoparticle for stabilizing the water-in-crude oil Pickering emulsion—application to a new oil recovery method: Viscosity increased-emulsion flooding

When crude oil is in-situ emulsified in reservoir by the injected fluid to form water-in-crude oil emulsion the fluid with higher viscosity than that of the continuous phase is obtained in the displacing front, which results in the decrease of mobility ratio and the increase of sweep volume. This is a new method for enhancing oil recovery via increasing viscosity of crude oil in emulsion flooding. To achieve this result, the high-performance Janus nano-emulsifier (HMJP) has been obtained in this paper, which employs the low-cost, environmental-friendly, and recyclable magnetic nano-Fe3O4 to be the core. Then, the relationship between the emulsifying crude oil performance and the wettability of this Janus nanoparticle has been discovered and the related interfacial stabilization mechanism is discussed by interfacial dilatation rheology. Results show that the synthesized HMJPs have strong magnetic property and can be recyclable. For the given crude oil in this paper, when 0.04% of Q-16 (the carbon number used is equal to 16) is dispersing in 0.08% of LAD-30 surfactant fluid the water content of emulsion has been 90% and the emulsion viscosity is 10732.3mPa•s, which also reached excellent oil recovery. The emulsifying crude oil performance of HMJP is strongly associated with its wettability. The inborn interface-property of HMJP, surfactant, and the active components in crude oil all play a key role to decide the wettability of HMJP in preparing water in crude Pickering emulsion. The wettability of the modified HMJP is more neutral the emulsifying performance is stronger.

Enhanced Oil Recovery in a Co-Culture System of Pseudomonas aeruginosa and Bacillus subtilis.

Microbial enhanced oil recovery (MEOR) is a promising technology for oil field extraction. This study investigated a co-culture system of Pseudomonas aeruginosa and Bacillus subtilis to increase MEOR efficacy. We analyzed bacterial growth, biosurfactant production, and crude oil emulsified performance under different inoculation ratios. Compared to single cultures, the co-culture system showed superior growth and functional expression, with an optimal inoculation ratio of 1:1. Quantitative assessments of the cell numbers and biosurfactant production during the co-culture revealed that rapid B. subtilis proliferation in early stages significantly stimulated P. aeruginosa growth. This interaction increased cell density and rhamnolipid production by 208.05% and 216.25%, respectively. The microscopic etching model displacement results demonstrated enhanced emulsification and mobilization of crude oil by the co-culture system, resulting in 94.48% recovery. A successful field application in a block-scale reservoir increased cumulative oil production by 3.25 × 103 t. An analysis of microbial community structure and function in different phases revealed that after co-culture system injection, Pseudomonas became the dominant genus in the reservoir community, with an average abundance of 24.80%. Additionally, the abundance of biosurfactant-producing and hydrocarbon-degrading bacteria increased significantly. This research and the application of the P. aeruginosa and B. subtilis co-culture system provide novel insights and strategies for MEOR.

Study on CO2 Injection Enhanced Oil Recovery Method and Buried Mechanism in Low Permeability Gas Reservoir

Study on CO2 Injection Enhanced Oil Recovery Method and Buried Mechanism in Low Permeability Gas Reservoir

Stability analysis of nanofluid with aluminum oxide and polyacrylamide for enhanced oil recovery: insight into experimental investigation

Stability analysis of nanofluid with aluminum oxide and polyacrylamide for enhanced oil recovery: insight into experimental investigation

Predicting CO2 and H2 Solubility in Pure Water and Various Aqueous Systems: Implication for CO2–EOR, Carbon Capture and Sequestration, Natural Hydrogen Production and Underground Hydrogen Storage

The growing energy demand and the need for climate mitigation strategies have spurred interest in the application of CO2–enhanced oil recovery (CO2–EOR) and carbon capture, utilization, and storage (CCUS). Furthermore, natural hydrogen (H2) production and underground hydrogen storage (UHS) in geological media have emerged as promising technologies for cleaner energy and achieving net–zero emissions. However, selecting a suitable geological storage medium is complex, as it depends on the physicochemical and petrophysical characteristics of the host rock. Solubility is a key factor affecting the above–mentioned processes, and it is critical to understand phase distribution and estimating trapping capacities. This paper conducts a succinct review of predictive techniques and present novel simple and non–iterative predictive models for swift and reliable prediction of solubility behaviors in CO2–brine and H2–brine systems under varying conditions of pressure, temperature, and salinity (T–P–m salts), which are crucial for many geological and energy–related applications. The proposed models predict CO2 solubility in CO2 + H2O and CO2 + brine systems containing mixed salts and various single salt systems (Na+, K+, Ca2+, Mg2+, Cl−, SO42−) under typical geological conditions (273.15–523.15 K, 0–71 MPa), as well as H2 solubility in H2 + H2O and H2 + brine systems containing NaCl (273.15–630 K, 0–101 MPa). The proposed models are validated against experimental data, with average absolute errors for CO2 solubility in pure water and brine ranging between 8.19 and 8.80% and for H2 solubility in pure water and brine between 4.03 and 9.91%, respectively. These results demonstrate that the models can accurately predict solubility over a wide range of conditions while remaining computationally efficient compared to traditional models. Importantly, the proposed models can reproduce abrupt variations in phase composition during phase transitions and account for the influence of different ions on CO2 solubility. The solubility models accurately capture the salting–out (SO) characteristics of CO2 and H2 gas in various types of salt systems which are consistent with previous studies. The simplified solubility models for CO2 and H2 presented in this study offer significant advantages over conventional approaches, including computational efficiency and accuracy across a wide range of geological conditions. The explicit, derivative–continuous nature of these models eliminates the need for iterative algorithms, making them suitable for integration into large–scale multiphase flow simulations. This work contributes to the field by offering reliable tools for modeling solubility in various subsurface energy and environmental–related applications, facilitating their application in energy transition strategies aimed at reducing carbon emissions.

Description of nonlinear viscous and viscoelastic properties of polyacrylamide solution under loading

Background. Currently, the solution of the problem of describing the rheological behavior of viscoelastic and nonlinear viscous properties of liquid and solid-like materials is far from perfect. For successful application of polymer systems to enhance oil recovery and for preparation of fracturing fluids and drilling fluids, knowledge of their rheological properties is necessary. Objective. To determine the nonlinear viscous and viscoelastic properties of polyacrylamide solution. Material and methods. We made an attempt to describe the rheological behavior of a polyacrylamide solution depending on the shear rate and on the loading time. A binomial rheological model was used to describe steady-state stresses at different shear rates, which showed a high degree of accuracy. To describe the stress from time, we proposed to use a numerical solution of a system of two differential equations representing the well-known Maxwell and Kelvin–Voigt equations. To describe the initial section of the curves for times less than 0.05 s, a model with a variable modulus of elasticity was used. Results. A high degree of correspondence of experimental and design stresses with a time of more than 0.05 s was achieved. The overall solution was achieved by combining two solutions based on shear rate and shear stress. Relationships with high correlation coefficients were found between the elastic modulus, viscosities of Maxwell and Kelvin and the shear stress and shear rate. Conclusions. We show that in addition to the “ordinary” shear rate determined by the rotation of the viscometer cylinder, it is necessary to consider an additional shear rate due to stress changes in time. Due to this approach, a description of the stress maximum and its displacement from the shear rate can be made. We note that the additional shear rate occurred immediately after the start of loading, rather than at the time of stress drop, as commonly believed.