Fluid Properties Research Articles

Effects of particle density and fluid properties on mono-dispersed granular flows in a rotating drum

Due to their simple geometric configuration and involved rich physics, rotating drums have been widely used to elaborate granular flow dynamics, which is of significant importance in many scientific and engineering applications. This study both numerically and experimentally investigates dry and wet mono-dispersed granular flows in a rotating drum, concentrating on the effects of relative densities, ρs−ρf, and rotating speeds, ω. In our numerical model, a continuum approach based on the two-phase flow and μI theory is adopted, with all material parameters calibrated from experimental measurements. It is found that, in the rolling and cascading regimes, the dynamic angle of repose and the flow region depth are linearly correlated with the modified Froude number, Fr*, introducing the relative density. At the pore scale, flow mobility can be characterized by the excess pore pressure, pf. To quantify the variance of the local pf, it is specifically nondimensionalized as a pore pressure number, K, and then manifested as a function of porosity, 1−ϕs. We find K(ϕs) approximately follow the same manner as the Kozeny–Carman equation, K∝ ϕs2/1−ϕs3. Furthermore, we present the applicability of the length-scale-based rheology model developed by Ge et al. [“Unifying length-scale-based rheology of dense suspensions,” Phys. Rev. Fluids 9, L012302 (2024)], which combines all the related time scales in one dimensionless number G, and a power law between G and 1−ϕs/ϕc is confirmed. This work sheds new lights not only on the rigidity of implementing continuum simulations for two-phase granular flows, but also on optimizing rotating drums related engineering applications and understanding their underlying mechanisms.

Test of the relation between temporal and spatial [formula omitted] by Knopoff et al.

The quality factor is a dimensionless measure of the energy loss per cycle of wave modes in an attenuation medium. Accurate measurement is important in various fields, from seismological studies to detect zones of partial melting to the geophysics of reservoirs to study rock properties such as porosity, fluid properties and saturation and permeability. In seismology, the quality factors measured for normal (standing) modes and propagating waves differ, as well those of equivalent experiments based on resonant rods and ultrasonic pulses performed in the laboratory. These measurements result in temporal and spatial quality factors respectively. A relationship between these two different quality factors and between the corresponding attenuation factors was proposed by Knopoff et al. sixty years ago. The conversion factor is basically the ratio between the phase velocity and the group velocity, while for the attenuation factor is the group velocity. We test these relations, which hold for low-loss solids, for body waves, using a Kelvin-Voigt rheology and a constant Q model, which provide explicit expressions of the temporal and spatial quality factors and velocities involved in these relations. The proposed theory provides the basis for a complete characterization of temporal and spatial quality factors and velocity dispersion based on arbitrary stress–strain relationships.

Physics-Informed Deep-Learning Models Improve Forecast Scalability, Reliability

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 4042557, “Physics-Informed Deep-Learning Models for Improving Shale and Tight Forecast Scalability and Reliability,” by Kainan Wang, SPE, Lichi Deng, and Yuzhe Cai, SPE, Chevron, et al. The paper has not been peer reviewed. _ In the complete paper, the authors present a workflow that combines probabilistic modeling and deep-learning models trained on an ensemble of physics models to improve scalability and reliability for shale and tight reservoir forecasting. Their approach is applied to synthetic cases and many wells in the Permian Basin. Through hindsight studies, these models have been demonstrated to generate realistic and diverse production curves, capture the physics of unconventional flow, quantify well-production-outlook uncertainty, and help interpretation of subsurface uncertainty. Introduction In the realm of unconventional asset development, scalable forecasting is a key component in forecast reliability. In recent years, data-driven machine-learning models and workflows have emerged as potent tools for predicting well performance, particularly in scenarios where wells share similar reservoir properties, completion designs, and operational conditions. A novel approach known as physics-informed machine learning (PIML) has gained prominence. These models leverage the strengths of machine learning while honoring the constraints imposed by physical laws. By incorporating observational, inductive, or learning bias, they bridge the gap between empirical data and fundamental physics. In this paper, the authors showcase the application of a PIML system tailored specifically for unconventional reservoirs. Their methodology involves the selection of an appropriate physics modeling framework, coupled with the development of multiple machine-learning models that augment the limited field data set. Data Acquisition and Generation Bottomhole pressure (BHP) data are key to reliable forecasting because they reflect constraints to well production. Downhole pressure gauges can provide measurements of BHP accurately, but these measurements are not always available. Numerical models can be used to correlate surface measurements to BHP with some accuracy, taking into consideration the well configuration and fluid properties, yet it is too time-consuming to develop such models for many wells in relation to the speed needed for unconventional reservoir development. An in-house machine-learning model was developed for BHP calculation to further augment the data set of gauge measurements and numerical modeling. Through a workflow that chooses the wells with higher-fidelity data as a training set, and careful calibration and iterations between incrementally adding wells of high-fidelity data to reduce uncertainty, the trained machine- learning model is able to predict BHP accurately for many more wells. Another type of engineering data important for reliable well-performance analysis and forecasting is reservoir-fluid description. In this study, the authors leveraged an internally developed pressure/volume/temperature (PVT) machine-learning model trained on proprietary PVT data, which was also shown to provide reliable predictions to key PVT properties such as saturation pressure, formation volume factor, and viscosity from limited inputs at the reservoir and separator level. These PVT models not only enhance scalability of any downstream forecasting models but also play a crucial role in physics-informed uncertainty analysis for these models.

Autonomous Inflow Control Valves Enable Better Water Control in Peru Oil Field

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218074, “Making Better Wells With Autonomous Inflow Control Valves for Water Control in the Flank of the Bretaña Norte Oil Field, Peru: A Case Study,” by Willy Garcia, SPE, J. Antonio Zegarra, SPE, and Edwar Bustamante, PetroTal Peru, et al. The paper has not been peer reviewed. _ Bretaña Norte is a heavy oil greenfield in a remote area of northeast Peru. The field development strategy was designed around horizontal wells and advanced completions with autonomous inflow control devices (AICDs). As a part of a technology evaluation program, autonomous inflow-control-valve (AICV) technology was selected for field trials because of its ability to autonomously shut off water based on fluid properties. A reservoir simulation study was conducted, and the expected performance of AICV was compared with other AICD technologies installed in the field, indicating potential benefits related to better reservoir management. Field Description Bretaña Norte is an onshore field in the Peruvian Amazon. The Vivian formation is the main reservoir of the Bretaña Norte field and consists entirely of fluvial deposits composed of massive, moderately sorted, fluvial sandstones with thicknesses ranging from 40 to 200 ft. The Vivian formation is subdivided into Vivian S1 and Vivian S2, but only the Vivian S2 formation has been exploited to date. Heavy oil is produced from the Vivian S2 formation (18–19 °API and 25 cp), which features reservoir permeability ranging from 1 to 4 darcies. An active bottom aquifer of greater than 400-ft thickness was encountered under the60-ft oil column of the reservoir, posing a difficult production challenge to the operator: how to handle high volumes of water production that must be reinjected into a different formation. The Bretaña Norte field began production in 2018 with a few initial deviated wells with electrical submersible pumps (ESPs). The first horizontal well completed with standalone screens (SAS) experienced early water breakthrough. Thus, the operator opted for advanced completions with screens and AICDs in 2019. Between 2019 and 2023, 11 wells were completed with different AICD technologies. Even though initial results were positive, such outcomes have been highly dependent on the structural position of the wells. In 2022, a trial well was completed with the AICV technology in the flank of the reservoir, significantly closer to the oil/water contact (OWC), to evaluate its performance under challenging conditions. AICV Technology The AICV is an AICD designed to modify its open-flow area according to the properties (viscosity and density) of the fluids flowing through it and to choke flow progressively as water cut or gas-volume fraction values increase. The AICV is fully reversible, meaning that, if changes in the fluids flowing through the valve occur, it will reopen or reclose accordingly. The AICV consists of two flow paths, the main flow path and the pilot flow path, with an approximate flow distribution of 97 and 3%, respectively. Fig. 1 presents a schematic of the AICV, including a heat map showing the pressure distribution across the different flow paths.

Optimization of geological carbon storage operations with multimodal latent dynamic model and deep reinforcement learning

Identifying the time-varying control schemes that maximize storage performance is critical to the commercial deployment of geological carbon storage (GCS) projects. However, the optimization process typically demands extensive resource-intensive simulation evaluations, which poses significant computational challenges and practical limitations. In this study, we presented the multimodal latent dynamic (MLD) model, a novel deep learning framework for fast flow prediction and well control optimization in GCS operations. The MLD model implicitly characterizes the forward compositional simulation process through three components: a representation module that learns compressed latent representations of the system, a transition module that approximates the evolution of the system states in the low-dimensional latent space, and a prediction module that forecasts the flow responses for given well controls. A novel model training strategy combining a regression loss and a joint-embedding consistency loss was introduced to jointly optimize the three modules, which enhances the temporal consistency of the learned representations and ensures multi-step prediction accuracy. Unlike most existing deep learning models designed for systems with specific parameters, the MLD model supports arbitrary input modalities, thereby enabling comprehensive consideration of interactions between diverse types of data, including dynamic state variables, static spatial system parameters, rock and fluid properties, as well as external well settings. Since the MLD model mirrors the structure of a Markov decision process (MDP) that computes state transitions and rewards (i.e., economic calculation for flow responses) for given states and actions, it can serve as an interactive environment to train deep reinforcement learning agents. Specifically, the soft actor-critic (SAC) algorithm was employed to learn an optimal control policy that maximizes the net present value (NPV) from the experiences gained by continuous interactions with the MLD model. The efficacy of the proposed approach was first compared against commonly used simulation-based evolutionary algorithm and surrogate-assisted evolutionary algorithm on a deterministic GCS optimization case, showing that the proposed approach achieves the highest NPV, while reducing the required computational resources by more than 60%. The framework was further applied to the generalizable GCS optimization case. The results indicate that the trained agent is capable of harnessing the knowledge learned from previous scenarios to provide improved decisions for newly encountered scenarios, demonstrating promising generalization performance.

Technology Focus: Sand Management (October 2024)

With the resurgence of drilling activities post-COVID-19, there is a growing interest in refining existing technologies and exploring new ones to discover cost-effective and reliable solutions for developing aged and more-challenging new reservoirs. Although approaches may vary slightly depending on the unique characteristics of reservoirs in different regions, the general trends are conceptually similar. Drilling longer wells, increasing the number of fracture stages, and completing multiple zones in complex stacked reservoirs, along with optimizing multilateral wells with sand control to enable long laterals in stacked reservoirs, have emerged as key focuses of the industry. Drilling longer wells introduces several challenges, including managing installation loads, ensuring proper wellbore cleanout, and ultimately producing effectively and uniformly from extended laterals that drill through heterogeneous reservoirs with varying sand facies. While liner flotation is effective in reducing installation loads and improving wellbore cleaning, it presents challenges when used in conjunction with conventional sand-control screens. Sand control and flow control are becoming more integrated to offer solutions for effective production from longer laterals. Flow segmentation helps prevent premature failures caused by gas or water breakthroughs or localized high rates causing erosion. Paper SPE 218074 is a good example of using flow-control devices to enhance the reliability and longevity of sand-control systems. Stacked reservoirs have always posed challenges in terms of zonal isolation and sand-control design. Higher fines content and silty sand with complex reservoir conditions leads to less interest in standalone screens because of the high risk of plugging and failure in such developments. Even though gravel packing is effective, it poses several technical and implementation challenges. The complexity of sandface completion, with varying sand sizes, pressures, and fluid properties, makes these wells particularly difficult to complete. Paper SPE 214914 offers a good case study of such a complex completion successfully implemented in the field. Despite all this, the fundamentals of screen design and implementation remain the same. Screen plugging remains one of the major challenges in the sand-control industry. Rigorous testing of sand-control media to verify retention properties, erosional resistance, integrity requirements for the installation-loading and lifelong-loading scenarios, and plugging resistance are critical aspects of any sand-control qualification. I strongly recommend reading paper IPTC 23690 for a detailed understanding of the screen-qualification process and the design of screens for target sand facies. Also, it is crucial to remember that no screen is completely immune to plugging. The unintended consequences of a change in drilling/completion fluid or cleanout process could lead to screen plugging. It is always important to test and validate the effect of any change in fluids or completion practices on sand-control performance. Recommended additional reading at OnePetro: www.onepetro.org. SPE 215070 A Comprehensive Review of Screen Plugging During Openhole Sand-Control Completions Installation: Causes, Consequences, and Best Practices by Maye Beldongar, SLB, et al. SPE 214934 Shunted Gravel-Pack Failures and How To Prevent Them by Carolina Latini, DuneFront, et al. SPE 215411 Performance of Bonded Bead Sand Screen as Remedial Sand Control in Highly Erosive Environment by Ashvin Avalani Chandrakant, Petronas, et al.

Volcanic tremor associated with successive gas emission activity at a boiling pool: Analyses of seismic array and visible image data recorded at Iwo-Yama in Kirishima Volcanic complex, Japan

Volcanic tremors are often observed during volcanic activity and volcanic eruptions, and their generation processes provide clues for understanding volcanic fluid activity underground and eruption dynamics. However, tremors are characterized by continuous oscillations that mask P- and S-waves; hence few studies have precisely located the source, which is the most fundamental information for understanding the generation mechanism. In this study, we focus on volcanic tremors excited by continuous gas emissions occurring at a vent called Y2a in Iwo-Yama, the Kirishima Volcanic Complex, Japan, to clarify the source process of the tremor as well as gas emission activity. We simultaneously observed the volcanic tremor by deploying a small aperture array consisting of six seismometers and the gas emission activity by using a newly developed visual IoT system that can be operated without commercial electricity. MUSIC analysis locates the tremor at depths ranging from the ground surface to approximately 200 m beneath the Y2a and Y2b vents, which are approximately 30 m apart, for approximately four months from November 2021 to February 2022. The source locations of the tremors in the 2 Hz (1.2–2.6 Hz), 4 Hz (3–4 Hz), and 5 Hz (4–5.5 Hz) ranges show some differences and changes with time. The source location tends to become deeper when the 2 Hz amplitude is large. The infrasound generated by gas emission activity is dominant in the tremor signals, which are recognized in the wave propagation velocity with an acoustic velocity of 330 m/s when the 2 Hz amplitude is small. The visual IoT system succeeded in detecting long-term changes in the gas emission activity, and we found that the 2 Hz amplitude of tremor was well correlated with the amount of hot water in the boiling pool of Y2a, which was controlled by precipitation and evaporation during non-rainy days. From these observations, we infer that the volcanic tremor is generated by resonance of volcanic gas and hot water in a crack-like structure beneath Y2a. The resonance was triggered by the counterforces of the gas emissions in the boiling pool, and the infrasound was dominant during periods of hot water depletion in the boiling pool. Temporal changes in the source depths may be caused by changes in the fluid properties, configuration of the resonator and/or the strengths of the underground sources and infrasound. Our simultaneous observations of seismic array and visual IoT system clarify that even the continuous gas emission activity that looks stable is controlled by external sources such as precipitation.

The Influence of Gas Lift on Oil Drainage Area in Reservoirs

Abstract Gas lift is a widely employed artificial lift method in the oil and gas industry, with the potential to significantly impact oil recovery from reservoirs. This study investigates the effect of gas lift on the oil drainage area within reservoirs, aiming to enhance our understanding of its role in reservoir management. Using advanced reservoir engineering and simulation techniques, the research explores the dynamics of gas lift and its influence on the accessibility of hydrocarbon resources. The study provides a comprehensive analysis of gas lift parameters, including gas injection rates, depths, and configurations, and their collective impact on the drainage area. It also considers the interplay between gas lift operations and reservoir characteristics such as permeability, porosity, and fluid properties. Findings from this study reveal that gas lift can effectively expand the drainage area by reducing bottomhole pressures and facilitating the movement of oil within the reservoir. This expansion enables the recovery of hydrocarbons from previously untapped regions, resulting in improved oil production. The research underscores the importance of optimizing gas lift design to maximize reservoir performance. Additionally, the study addresses operational challenges associated with gas lift, including gas allocation, injection optimization, and equipment reliability. It provides insights into the economic and operational considerations of gas lifts, offering valuable recommendations for reservoir management. The outcomes of this research contribute to a deeper understanding of how gas lift influences the oil drainage area in reservoirs, providing valuable insights for reservoir engineers, operators, and industry professionals involved in oil production. This knowledge supports informed decision-making to optimize oil recovery, reservoir performance, and the efficient use of gas lift technologies.

Research of productivity and interlayer interference mechanism of multilayer co-production in reservoirs with multi-pressure systems

Abstract Due to the differences of physical and fluid properties in vertical oil layers, the interlayer contradictions are prominent and affect the reservoir utilization degree seriously. Therefore, the coordination between reasonable bottom-hole flow pressure and optimal production, as well as the reduction of interlayer interference are the primary concerns during the co-production of multi-layer oil reservoirs. Based on the reservoir engineering and fluid mechanics in porous media theory, this work adopt the comprehensive pressure system and consider the interlayer interference to establish a multi-branch horizontal well productivity model and interlayer interference mathematical model. By analyzing the main controlling factors and interference mechanisms, this article establishes a pattern of interlayer interference, and improves the quantitative characterization interlayer interference theory in multi-layer combined mining. The study has shown that: (1) The interlayer interference is beneficial for balancing the production of different layers and improving development efficiency, it is greatly affected by interlayer heterogeneity; (2) When the number of layers exceeds 2 layers, the interference coefficient increases; With the increase of the layer thickness, the thicker oil layers have higher productivity, and the thickness of layer has a significant effect on the production of low-pressure layer; When the production pressure difference increases, the interlayer interference can be reduced; (3) The interlayer interference mathematical model constructed in this paper has high prediction accuracy and strong practicality, which has theoretical guidance significance for the division of strata in comprehensive adjustment of reservoirs.

Molecular simulation of gas entrapment near a nanoscale cavity: The interplay of surface wettability, cavity shape, and gas type

Surface cavities play a crucial role in trapping and stabilizing gases, a phenomenon that can be used to facilitate applications in separation and drying processes. Understanding surface characteristics in relation to fluid-surface interactions is essential for designing interfacial properties that enable effective processes. In this work, we adopt a molecular simulation approach to investigate gas adsorption and entrapment in surface defects (cavities), focusing on the influence of surface wettability, cavity shape, and gas type. For this purpose, two types of silica-based surfaces with different levels of wettability (methylated and hydroxylated, with the former having lower water wettability), two cavity shapes with identical opening width and depth (V-shaped and square-shaped), and two types of gas (carbon dioxide and nitrogen) are considered. Our observations indicate that a stable gas nanobubble forms when a methylated surface combines with a square-shaped cavity, regardless of the gas type. In contrast, for hydroxylated surface, gas type becomes important; in a square-shaped cavity, nitrogen forms a stable nanobubble while CO2 is trapped in a monolayer fashion. The interfacial forces between the gas and surface which affects gas configuration near the surface, along with the gas molecules’ self-interaction manifested by solubility, are key to the different entrapment modes for N2 and CO2. Moreover, the square-shaped cavity exhibits better capability in trapping gas compared to the V-shaped cavity due to its higher surface area and smaller opening-to-interior ratio. The results of our molecular simulations can guide the design of surface features and processing systems to modify gas entrapment modes and stabilize nanoscale gas bubbles without altering thermodynamic conditions or fluid properties.

A coupled fractal model for predicting the relative permeability of rocks considering both irreducible fluid saturation and stress effects

The relative permeability of rocks is an essential parameter for evaluating two-phase flow characteristics and plays an important role in engineering fields such as resource exploitation. To this end, a mathematical model for predicting relative permeability was first developed based on an equivalent capillary model and fractal theory. The proposed model considers the irreducible fluid saturation under stress and quantifies the influence of the pore structure characteristics on the relative permeability. This model was then compared with relevant experimental data and existing theoretical expressions to verify its validity. Finally, the factors affecting the two-phase seepage characteristics were discussed. The results show that the irreducible fluid saturation is intimately connected to the fractal dimensions, pore size, fluid viscosity, pressure drop gradient, and elastic modulus. Fluid properties and pore structure characteristics are the main factors affecting relative permeability. The wetting phase relative permeability is more sensitive to pore structure and irreducible fluids. Increased effective stress increases irreducible fluid saturation, reduces two-phase flow capacity, and significantly decreases the relative permeability of wetting phase fluids. Increased elastic modulus and Poisson's ratio decrease the irreducible fluid content under stress and increase the permeability.

Cyclic flow cut-off characteristics of gas-liquid two-phase flow in pipeline-riser system and prediction of its occurring condition

In offshore oil and gas fields, the prediction of gas-liquid two-phase flow pattern is of great importance for the design and operation of pipeline-riser systems. However, no special attention was put on the mechanism of periodic flow cut-off at the riser outlet, which is an inherent characteristic of certain flow patterns directly related to operation safety, in the study of flow pattern transition. In this study, differential pressure signals are used to explore the internal correlation between the flow cut-off of gas and/or liquid phase at the riser bottom and the riser outlet. The flow patterns are classified based on continuous flow or flow cut-off at the riser outlet. Then, the flow pattern transition mechanisms are studied from the view of the condition under which flow cut-off will appear. At high gas and low liquid velocities, the mechanism can be explained by a conventional theory; while at high gas and high liquid velocities, dissipation of hydrodynamic slugs becomes the major reason for flow pattern transition; and a unified model is introduced to predict the dissipation. At low gas and high liquid velocities, the condition for gas-liquid eruption can still describe the flow pattern transition, but it is modified by the slug dissipation model. At higher pressure, the lasting time of gas cut-off at the riser elbow becomes shorter, and a threshold can be set to decide whether it can be ignored. The predicted results are in good agreement with the flow pattern maps under different pipeline structures and fluid properties, and the reason why flow cut-off disappears in the experimental loop at high pressure of 10 MPa is successfully explained.

Experimental and theoretical study on liquid film thickness of upward annular flow in helically coiled tubes

The liquid film thickness is crucial for studying the thermal hydraulic mechanism of the annular flow region in helically coiled tubes (HCTs). This paper introduces a refined experimental study on the liquid film thickness of annular flow in HCTs, utilizing a newly developed liquid film sensor. The experimental results indicate that the smaller coil diameters and pitches result in thinner average liquid film thicknesses. The average liquid film thickness decreases with increasing superficial gas velocity and decreasing superficial liquid velocity. However, the liquid film thickness at different circumferential positions on the cross-section of the tube exhibits varying sensitivities to superficial gas and liquid velocities. The experimental data reveal that the existing typical correlation formula for the average liquid film thickness of annular flow in straight tubes does not apply to HCTs. Consequently, a new prediction model is proposed for the average liquid film thickness of the annular flow region in HCTs, based on the modified Froude number, modified Dean number, Ekman number, and Reynolds number. This model comprehensively incorporates the structural characteristics of HCTs and fluid properties, and its validity is verified through the utilization of available and current data in the literature.

Electro-osmotic flow instability of viscoelastic fluids in a nanochannel

The study of the complex rheological properties of viscoelastic fluids in nanochannels will facilitate the application of nanofluidics in biomedical and other fields. However, the flow of viscoelastic fluids in nanochannels has significant instabilities, and numerical simulation failures are prone to occur at high Weissenberg numbers (Wi). In this study, the simplified Phan-Thien-Tanner viscoelastic fluid model is solved using the log-conformation tensor approach, and the effects of rheological parameters of the viscoelastic fluid, such as the Weissenberg number (Wi), extensibility parameter (ε), and viscosity ratio (β), on the flow characteristics and flow instability within the nanochannel are investigated. The results indicate that the variation of rheological parameters of viscoelastic fluids has a significant effect on the flow state and flow instability of fluids in nanochannels. When the rheological parameters are in a specific range, the flow velocity and outlet current in the nanochannel exhibit relatively regular periodic fluctuations. As the flow transitions from an up-and-down moving single-vortex state to a symmetric double-vortex state, the average velocity of the central axis in the nanochannel is increased by about 15%. Furthermore, when Wi increases from 150 to 400, the length and height of the vortex increase by 50% and 100%, respectively.

Comparison of the characteristics of small intestinal fluid from white-feathered and yellow-feathered broilers

The objective of this study was to compare the properties of small intestinal fluid (SIF) from white- and yellow-feathered broilers fed variable dietary CP to test the hypothesis that digestive enzymes sourced from the SIF of yellow-feathered broilers could serve as a viable alternative for preparing in vitro SIF specifically for white-feathered broilers. Ten Arbor Acres Plus broilers (32 days of age) and 20 Chinese yellow chickens (51 days of age) were fitted with jejunal cannulas and assigned to dietary treatments as follows: 1) white-feathered broilers (BW of 4.08 ± 0.39 kg) fed diet 1 with CP of 19.88 %, 2) yellow-feathered broilers (BW of 2.89 ± 0.27 kg) fed diet 1, and 3) yellow-feathered broilers (BW of 2.84 ± 0.20 kg) fed diet 2 with CP of 16.32 %. Each treatment contained 10 replicates with 1 broiler in each replicate. Digestive enzyme activities, ion concentrations, pH, 16 amino acid (AA, excluding Tyr and Trp) contents, molecular weight distribution (MWD) of protein, hydrolysis rates on wheat starch, corn starch, casein, and soybean protein concentrate, and in vitro digestible energy of corn, soybean meal, and corn gluten meal were evaluated for SIF. Activities of chymotrypsin and amylase, pH, concentrations (mg/mL) of total amino acid (TAA) and 13 AA (excluding Pro, Cys, and Glu), and hydrolysis rates in casein or soybean protein concentrate were greater (P < 0.05), whereas MWD of protein from 19 to 23 kDa was lower (P < 0.05) in the SIF of yellow compared to white-feathered broilers fed diet 1. Furthermore, activities of chymotrypsin and amylase, concentrations of Na+, and Cl−, MWD of protein from 15 to 18 kDa were greater, while concentrations of K+ were lower in the SIF of yellow-feathered broilers fed diet 2 compared to white feathered broilers fed diet 1. Activities of chymotrypsin and amylase, K+ concentration, pH, TAA and 13 AA (excluding Pro, Cys, and Glu), hydrolysis rates in casein or soybean protein concentrate increased (P < 0.05), while concentrations of Na+ and Cl− (P < 0.05) decreased with dietary CP in SIF from yellow-feathered broilers. This experiment demonstrated diet composition and breed modulate digestive enzyme activities, ions (Na+, K+, Cl−), pH, and AA concentrations in the SIF. Our findings revealed no substantial difference in the hydrolytic characteristics of SIF from white-feathered broilers fed diet 1 and yellow-feathered broilers fed diet 2. Consequently, it is feasible to use digestive enzymes extracted from the SIF of yellow-feathered broilers to prepare simulated SIF for in vitro digestion of white-feathered broilers.

Evaluation of movable fluid and controlling factors in lacustrine gravity-flow tight sandstone reservoirs: Implications for predicting reservoir quality

Lacustrine gravity-flow tight sandstone reservoirs are rich in petroleum resources, and the presence of movable fluids is essential for the efficient recovery of tight oil. However, characterizing the properties of movable fluids and predicting their content are challenging due to the limited data available on these fluids. To address this research gap, it is imperative to conduct a comprehensive study on the distribution patterns and controlling factors of movable fluids within the lacustrine gravity-flow tight sandstone reservoirs of the Chang-7 Member in the Heshui region of the Ordos Basin. The study utilized a range of analytical techniques, such as thin section analysis, scanning electron microscopy (SEM), high-pressure mercury injection (HPMI), constant-rate mercury injection (CRMI), and nuclear magnetic resonance (NMR). We identified three distinct lithofacies and three types of pore-throat spaces within these lacustrine gravity-flow sandstones. The highest amount of movable fluid was observed in the submicron pore throats, followed by nanopore throats, while the micron pore throats exhibited the lowest amount. Our analysis indicates that petrophysical parameters, mineral composition, and pore throat structures collectively influence the content of movable fluids. Specifically, quartz and feldspar content are positively correlated with the movable fluid content, while clay and carbonate cement content are negatively correlated. Fine sandstones with massive bedding typically have a high content of movable fluids, which is associated with elevated quartz and feldspar content. In contrast, very fine sandstones to siltstones with parallel or ripple beddings have a very low content of movable fluids, characterized by high levels of carbonate and clay cementation. The study also suggests that the lower limit of the pore throat radius of movable fluid is about 0.03 μm. These findings offer novel insights for evaluating and predicting high-quality lacustrine gravity-flow tight sandstone reservoirs, enabling more effective exploration and development strategies.

A bi-component model to assess the rheology of soft cellular aggregates probed using the micropipette aspiration technique

The micro-pipette aspiration technique is a classical experiment used to characterize the physical properties of inert fluids and biological soft materials such as cellular aggregates. The physical parameters of the fluid, as viscosity and interfacial tension, are obtained by studying how the fluid enters the pipette when the suction pressure is increased and how it relaxes when the suction pressure is put to zero. A mathematical model representative of the experiment is needed to extrapolate the physical parameters of the fluid-like matter; however, for biological materials as cells or cell aggregates these models are always based on strong starting hypotheses that impact the significance of the identified parameters. In this article, starting from the bi-constituent nature of the cell aggregate, we derive a general mathematical model based of a Cahn-Hilliard-Navier-Stokes set of equations. The model is applied to describe quantitatively the aspiration-retraction dynamics of a cell-aggregate into and out of a pipette. We demonstrate the predictive capability of the model and highlight the impact of the assumptions made on the identified parameters by studying two cases: one with a non-wetting condition between the cells and the wall of the pipette (classical assumption in the literature) and the second one, which is more realistic, with a partial wetting condition (contact angle θs = 150°). Furthermore, our results provide a purely physical explanation to the asymmetry between the aspiration and retraction responses which is alternative to the proposed hypothesis of an mechano-responsive alteration of the surface tension of the cell aggregate. Statement of SignificanceOur study introduces a general mathematical model, based on the Cahn-Hilliard-Navier-Stokes equations, tailored to model micro-pipette aspiration of cell aggregates. The model accounts for the multi-component structure of the cell aggregate and its intrinsic viscoelastic rheology. By challenging prevailing assumptions, particularly regarding perfect non-wetting conditions and the mechano-responsive alteration of cell surface tension, we demonstrate the reliability of the mathematical model and elucidate the mechanisms at play, offering a purely physical explanation for observed asymmetries between the aspiration and retraction stages of the experiment.

Synthesized Crosslinking Suspension Stabilizer for Spacer Fluid in High-Temperature Conditions: Synthesis, Behavior, and Mechanism Research

Summary High-temperature stability of spacer fluid is a vital prerequisite to ensure the safety of cementing operations in deep or ultradeep wells. Faced with this problem, the thermal stability of the suspension agent in the spacer fluid at high temperatures is improved from the aspects of polymerization monomer and molecular chain. A terpolymer SAD was synthesized by free radical polymerization of sodium styrene sulfonate (SSS), acrylamide (AM), and N, N’-diethylacrylamide (DEAA) in aqueous solution. The name of the terpolymer, SAD, is the initial letter composition of the three polymerization monomers. Polyethyleneimine (PEI) can improve the molecular chain structure of SAD by transamidation reaction with the amide group in SAD, so a high temperature suspension agent PSAD (polyethyleneimine + SAD) was obtained by compounding PEI with SAD. The structure and properties of PSAD were characterized by Fourier infrared spectroscopy, hydrogen nuclear magnetic resonance (NMR) spectroscopy, gel permeation chromatography, X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis, scanning electron microscopy (SEM), and viscosity test. In addition, the comprehensive properties of the spacer fluid under the action of PSAD are evaluated. The results showed that the crosslinking degree of PSAD gradually increased with the increase in temperature. After aging at 200°C, the decomposition temperature of PSAD was 305°C, which show terrific thermal stability. At the same time, the spacer fluid prepared by PSAD not only has excellent rheological properties in the range of 90 ~ 200°C but also keeps the density difference between the upper and lower parts of the slurry less than 0.02 g/cm3 and the filtration loss of the slurry less than 50 mL.

Multiscale rheology from bulk to nano using a quartz tuning fork-atomic force microscope.

Rheological characteristics exhibit significant variations at nanoscale confinement or near interfaces, compared to bulk rheological properties. To bridge the gap between nano- and bulk-scale rheology, allowing for a better and holistic understanding of rheology, developing a single experimental platform that provides rheological measurements across different scales, from nano to bulk, is desirable. Here, we present the novel methodology for multiscale rheology using a highly sensitive atomic force microscope based on a quartz tuning fork (QTF) force sensor. We employ microscale and nanoscale shear probes attached to the QTF, oscillating parallel to a substrate surface for rheological measurements as a function of the tip-substrate distance with sub-nanometer resolution. Silicone oils with viscosities ranging from 5 cSt to 10 000 cSt are used as calibration samples, and we have successfully derived the bulk rheological moduli. Furthermore, an increase in modulus is observed within the regime of tribo-nanorheology at distances less than 50nm from the surface. Through such multiscale measurements, it is confirmed that this increase is due to the formation of a layered structure of silicone oil polymers on the solid surface. These results provide a comprehensive understanding of the tribo-rheological properties of complex fluids across different scales.

Why gravity improves waterflood recovery in oil-wet and mixed-wet reservoirs

Most past experimental and numerical research on water flooding has demonstrated a reduction in oil recovery in gravity dominated flow: gravity leads to the water slumping to the bottom of the reservoir with earlier water breakthrough and poor sweep efficiency. However, these studies were all performed on strongly water-wet systems: wherever the water has gone, the oil is at residual saturation so a reduction in sweep efficiency gives a reduction in recovery. In reality few if any reservoirs are strongly water-wet. If the rock is mixed or oil-wet, gravity improves the local displacement efficiency. Gravity reduces the mobility of injected water forcing downward water movement and better oil displacement laterally. When gravity dominates, once water reaches the bottom of the reservoir, it moves upwards in a gravity-stable displacement, with improved local displacement efficiency that can be quantified by linear Buckley-Leverett analysis. We show, using fine-grid simulations of water flooding in a two-dimensional homogeneous vertical cross-section with typical fluid and rock properties, that the overall recovery after ∼0.3 pore volumes of water injected is higher than without gravity for heavy oil-wet (unfavourable mobility) applications. This improvement is greater in light oil-wet (favourable mobility) applications and occurs even before water breakthrough counteracting the negative effect of poor sweep efficiency. Simulations on a heterogeneous reservoir model representing an oil field from the Middle East confirmed the significance of gravity on improving the displacement and overall oil recovery. The same considerations should pertain in reverse for gas storage: storage efficiency improves in gravity dominated flow.