bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Approach Towards Flow Diagnostic in High-Rate Gas Wells
Authors: Marin J. D. , Chacon A. Castro , Almeyda O. , Lopez L. , Quintana J. E. , Gonzalez J. W. , Linares A. J. , Perez J. , Schoepf V. , Abbassi L.
Published: September 2024

High gas rate wells flowing up to 80 MMscfd pose challenges for flow diagnostics. Conventional methods for measuring gas and water holdups, such as local electrical probes, fail in these extreme conditions due to the extremely small droplets and hydrodynamic effects. Approaches based on fluid column density measurements suffer from large inaccuracies due to friction effects. The paper describes the sensor technology and field results from a high gas rate well with small water cut and complex flow regime.

To overcome these challenges, an operating company worked with a service and manufacturing company to improve a compact toolstring capable of delivering reliable flow data (holdups and phase velocity) for phase allocation over an interval with multiple zones and different fluid properties. The toolstring developed is shorter than conventional tools (just over three foot long) and causes minimal flow disturbance. Azimuthal phase holdups and velocities are collocated with one foot away auxiliary measurements of pressure, temperature, MEMS Magnetic Locator (MML) for casing collar detection and depth correlation, tool orientation, and deviation. The flow array sensors consist of triphasic optical probes, conductivity probes, micro-capacitances, Doppler, and wide-range robust micro-spinners.

Segregated flow with water recirculation was observed. The micro-capacitances provided the most reliable source for water holdup while the electrical probes in mist flow, as expected, stopped detecting water at flow speeds of 2 m/s. The triphasic optical probes showed good gas hold up measurements at the whole range of flow velocities in the well and responded to a small water entry in the middle of the perforated zone. All micro-spinners rotated well throughout the survey even at the highest rate. The radar sonde detected water droplets down to micrometer size using the retro diffusion of light electromagnetic signal at a distance from the sensor surface. While the EM radar senses water movement inside the mist flow, the Doppler sensors allowed to monitor movement in the water dominant leg at the well bottom. Thanks to integrating all types of sensors physics, a robust flow diagnostic allowed the operator to understand the water and gas entries, while the conventional sensors could not, and consider remedial actions for water shutoff. The present sensor configuration and tool string can be used as reference for logging in the same field or similar flow conditions.

In order to detect water, two novel sensors were developed: micro-capacitance probes to measure water holdup and electromagnetic radar for measuring flow speed. The standalone radar module operates in high velocity flow and does not require direct contact between droplets and the sensing element, as micrometer size water droplets can be detected with the retro diffusion of light EM signal at a distance from the sensor surface.
Integrated Framework for Proactive Sand Management: Leveraging Offset Well Data, Formation Stability Assessment, and Predictive Sand Transport Simulation
Authors: Vo Nghia Tri , Nguyen Hong Viet , Luong Chi Van
Published: September 2024

This paper addresses the challenge of sand production impacting well productivity. Authors propose a novel, integrated approach for proactive sand management that combines offset well performance analysis, geomechanics, and sand transport modeling. This methodology aims to minimize sand production for enhanced well productivity, develop tailored well designs with appropriate sand control methods for specific reservoir challenges, improve understanding of reservoir dynamics and sand transport mechanisms and optimize well production strategies.

Our approach leverages the following steps:

Offset Well Data Analysis: Production histories, completion types, and reservoir properties of existing offset wells are analyzed to identify factors influencing sand production and successful sand control strategies. Geomechanical Assessment: Separate geomechanical studies are used to assess formation stability under varying drawdown scenarios. This establishes safe operating limits to minimize formation instability and sand mobilization. Tailored Well Design: Based on the understanding of reservoir and sand behavior, well designs are developed with appropriate sand control methods (determined in separate studies) to address the unique challenges of the target reservoir. Production performance analysis: Potential fluid movement between formations is investigated using crossflow analysis techniques. This enhances reservoir understanding and optimizes production strategies. Sand Transport Modeling: Advanced transient simulators are used to build sand transportation models, predict potential sand production and blockage risks for multiple grain sizes and operational scenarios. Proactive measures and targeted interventions are then outlined for these potential situations.

This integrated approach offers a new standard in proactive sand management. It leverages offset well data, promotes a deep understanding of reservoir dynamics, facilitates tailored well design, predicts sand transport, and incorporates crossflow analysis.

This approach distinguishes itself by combining traditionally separate analyses. It integrates offset well analysis, geomechanics, and sand transport modeling for a holistic understanding of sand management challenges. It incorporates crossflow analysis, previously underexplored in sand management, to enhance reservoir understanding and production strategies. It focuses on proactive measures and targeted interventions for sand transport management. By implementing this comprehensive approach, operators can significantly improve well performance and optimize reservoir development.
Assessing Flow Potential Risk in Shallow Zones
Authors: Piazza R. , Netto P. , Grell A. P. , Fernandes L. , Schuck G.
Published: September 2024

Maintaining integrity is a major concern throughout the lifecycle of a well, especially during the decommissioning stage. Regulatory requirements mandate that barriers be established to prevent the flow of fluids to the surface, and that these barriers reconstitute the cap rock above intervals deemed to have flow potential. This can lead to extremely complex projects in scenarios where shallow zones distant from the reservoir are classified as having flow potential. Accurate characterization of shallow zones can have an outsize impact on the costs and operational challenges of the abandonment. Additionally, because decommissioning constraints must already be considered from as early as the drilling stage, these characterizations may influence decisions ranging from well design and completion to the field development project.

Characterizing the flow potential of shallow zones is inherently challenging, due to the scarcity and uncertainty of the data from these intervals. An exceedingly conservative approach can lead to abandonments that are not only costly, but that might also carry unnecessary operational hazards. On the other hand, not being sufficiently conservative increases the risk of an eventual leakage to the environment. Hence, the development and application of a consistent risk-analysis methodology is essential for operators.

The methodology presented is based on an ALARP approach and aims to quantify the likelihood and severity of an eventual outflow of fluid from the well after its abandonment, thus determining the level of risk associated with each interval and allowing for appropriate actions to be taken. The severity classification of a leakage event is based on the characteristics of the fluid present in the interval and on a stochastic estimate of the eventual volume that would flow to surface, supported by an analytical model that couples reservoir and wellbore flow behavior. Meanwhile, the likelihood is defined by the probability that such a leak would occur, based on a set of direct and indirect evidence available, and on the level of confidence associated with the data.

The application of this methodology has proven to be quite robust. It has streamlined the evaluation of individual intervals across various scenarios by providing a systematic approach that different teams can easily and consistently follow and has increased confidence in the decision-making process. Consequently, several recent wells were able to be decommissioned through simpler, safer configurations, and the drilling of several prospective wells was made viable due to less exigent isolation requirements.

Given the uncertainty related to the flow potential of shallow intervals and the consequences of underestimating or overestimating the risks associated with their characterization, it is vital that practical experiences and novel modeling strategies be shared and discussed by the community, to enhance the safety of well operations.
Smart Product to Cure Fluid Losses in Drilling Operations
Authors: Cracolici F. , Minelli M. , Vailati M. , Baretti S. , Iorio V. S. , Poloni R. , Sabatino L. M. F. , Goffredi G. , Valvo L. Lo , Bedogni E. , Alqutt Marwa , Napoleone L. L.
Published: September 2024

The project aims to develop a smart product for losses, different from the traditional approach, to control partial and total fluid losses in drilling operations. The developed smart product for losses is customized to reduce the non-productive time (NPT) and to improve the operation efficiency in compliance with oilfield safety requirements and industry standards.

This smart product for losses was engineered and validated both by operator and chemical provider partner's research technology laboratories, in order to verify the applicability range in water base mud (WBM) and oil base mud (OBM) environmental.

The smart product for losses is a bi-component fluid mixture, consisting of two parts: monomers blend and activator. These monomers and activator mixture show water-like rheological properties and are capable of becoming a stiff solid after a reaction activated by the temperature. The activation temperature can be regulated based on single application needs. This smart product for losses is pumpable throughout the drill string safely and becomes quickly a stiff solid when in contact with the formation temperature, creating a solid barrier in the well with consequent stop of drilling fluid losses.

The bi-component system has been designed with a series of laboratory tests to find the best mixture of monomers and activator. Once the formulation has been fixed, prior to moving on first field trial, confirmatory test campaign has been performed to ensure the proper functioning at the candidate well environmental condition. The first field trial was done in a depleted well ready for Plug & Abandonment, to verify fluid mixability and pumpability with conventional oilfield equipment in a real-life scale and verify proper product setting at well condition. All achievements for the test were satisfying and allowed the project to move to the next step, a test on a well with high probability to face out of total losses scenario during drilling operations. With this second test, the objective was to confirm the reliability of the bi-component system in a loss scenario during the drilling operation. Similar to the first field test, this test while drilling also achieved good results with the confirmation of capability of smart product for losses to properly setting on a open hole well bore condition, confirming the smart product's consistency.
Modeling of Multiphase Flow In Gas-Condensate Wells Under High Gas-Liquid Ratio Conditions and Field Application
Authors: Hong Jiajun , Wang Zhihua , Wang Cong , Zhang Jiuxiang , Qi Xiangdong , Ling Kegang
Published: September 2024

Currently, with continuous innovation of gas-condensate reservoir development technology, the production of gas-condensate and light oil has rapidly increased, making gas-condensate play an important role in the global petroleum industry. However, due to the deeper burial depths of gas-condensate reservoirs under high gas-liquid ratio condition, temperatures and pressures are much higher than conventional reservoirs. At the bottom of the wellbore, the gas-condensate system typically exists in a gaseous state. The retrograde condensation phenomenon is often observed during the production process of such gas-condensate wellbore. Especially when heavy components are present in the gas-condensate well,the appearance of wax particles, and complex multiphase flow characteristics with gas, liquid, and solid phases mixed flow are formed. These complex phase change characteristics of multi-alkanes coupled with multiphase flow patterns may have varying degrees of impact on production operations, from minor to severe.

Based on existing phase equilibrium models of multi-alkanes, this study fully considers wax appearance and dynamic changes in gas-liquid ratio caused by retrograde condensation. By coupling the multiphase flow characteristics of gas-condensate wells with the phase change process of gas-liquid-solid components under high gas-liquid ratio conditions, a mathematical model was established to predict multiphase flow in gas-condensate wells. This model not only reveals the phase change behaviors and wax appearance characteristics in gas-condensate wellbore with high gas-liquid ratio but also determines the critical wellbore depths at which the gas phase transitions to the liquid phase and wax appearance. It reliably predicts the composition of gas-liquid-solid phases at different wellbore depths. As the wellbore depth decreases, phase changes occur in sequence with decreasing molecular weight, appearing liquid and solid phases. The wax particles of solid phase are mainly composed of C33* (C33 to C40)and C25*(C25 to C32), while the liquid phase formed by the retrograde condensation is primarily composed of C17*(C17 to C24)and C9*(C9 to C16).

Additionally, it establishes a general correlation for predicting pressure drop, temperature drop, and wellbore depth in high gas-liquid ratio condensate wells, and the model's error is controlled within a 5% range by validating with actual data. Finally, the model calculation results determined the flow pattern transition process as follows: from single-phase gas flow at the bottom to gas-liquid phases mist flow and gas-liquid-solid phases mist flow towards the wellhead, and in conjunction with the supercritical state of light hydrocarbons to provide an explanation for the relationship between multiphase flow structure and wellbore pressure drop.
Characterization of Cement’s Temporal Mechanical Properties Under Simulated Downhole Conditions
Authors: Meng M. , Frash L. , Carey J. W. , Li W.
Published: September 2024

The evolution of cement mechanical properties is crucial for the performance of zonal isolation and determining the wait-on-cement period. To address this, a triaxial testing facility is developed that directly measures cement static elastic modulus and Poisson’s ratio of cement under in situ conditions. The accuracy of this facility was validated by measuring the bulk modulus of water. To obtain the temporal evolution of cement mechanical properties, an unloading-loading cycle every 30 mins was used from the beginning to the end of the experiment. An amplitude of 10 MPa during cyclic loading guarantees that the cement is in the elastic stage. The theory of poroelasticity was applied to estimate cement elastic modulus and Poisson’s ratio. A 7-day experiment was conducted under axial stress cycling between 40 MPa and 30 MPa, with a confining stressof 25 MPa. The Class G Cement, with a water-cement ratio of 0.4,began to gel after curing for 350 minutes (min), with rapid strength growthoccurring between 400 to 2000 min. After this period, the cement’s elastic modulus stabilized between 47 and 55 Gigapascal (GPa), and its Poisson’s ratio reached 0.35. These values are significantly higher than those obtained from the conventional triaxial compression tests. Overall, our work provides one way to evaluate cement in situ mechanical properties, which can be highly valuable for geothermal and deepwater drilling applications.
Estimating Near-Wellbore Cooling Due to Drilling Circulation and its Effect on Drill Stem Test
Authors: Hasan Abu Rashid , Manikonda Kaushik , Jang Minsoo , Rahman Mohammad Azizur , Hashmi Gibran
Published: September 2024

When drilling oil, gas or geothermal wells, the temperature difference between the wellbore and the formation can have a significant impact on its surroundings. Fluid circulation after drilling to rid the wellbore of drilling mud causes significant cooling around the wellbore near the bottom-hole. Even after shutting the well in, it often takes a long time for this near-wellbore zone to get back to the original formation temperature. This zone of altered temperature around the wellbore can give rise to various phenomena. It may influence wellbore stresses that may cause wellbore instability in high temperature formations that may lead to formation breakdown, or loss of circulation, or even a false kick. It may also play a part during any formation testing procedures carried out right after drilling. In the initial stages of flow after perforation, during clean-up, fluid flows through this cooled near-wellbore zone and enters the wellbore at a lower than undisturbed formation temperature. Any inference about this early fluid’s properties or their flow rates needs to account for the near-wellbore cooling. The estimation of compressible fluid flow rate is further complicated during Drill Stem Tests (DSTs) due to the transient nature of the temperature profile and having to account for multiple fluid entry points. At the start of the production period or when the production rates are changed in multi-rate DSTs, thermal transients take much longer to stabilize than the pressure. Because DSTs are often conducted before the near-wellbore temperature has become stabilized, DSTs are also affected. Thus, estimates of the near-wellbore temperature is often important.

This paper presents a model for estimating near-wellbore zone (NWZ) temperature as a function of radial distance and time. Heat lost (or gained) by this zone due to circulation is used to establish temperature distribution in the affected zone using a line-source solution of the heat diffusivity equation.A recently developed model for circulating fluid temperatures in tubing and annulus for offshore wells allows us to estimate heat transfer from the formation to the circulating fluid in the well.Note that various approaches, including the Horner method, are available to estimate any heat recovery of the affected zone for a well that has been shut-in after circulation. The model allows the computation of fluid flow rates and their entering temperature in the wellbore at early times. These estimates can then be used as inputs in DST analysis for more accurate characterization of the reservoir. Thus, the model impacts the deliverability results and in turn affects project economics. The model is validated using a set of field data.
Unraveling Damage Variables in Hot Dry Rocks: An Optical Investigation of Geothermal Rocks from UTAH FORGE
Authors: Nath F. , Cabezudo E.
Published: September 2024

Geothermal resources are worldwide renowned for their sustainable and clean attributes. The US Department of Energy (DOE) estimates that harnessing only 0.1% of Earth's geothermal energy could support mankind for two million years. Enhanced geothermal systems (EGS) are highly acclaimed for their ability to extract heat from hot, dry rock. However, issues remain in assuring safe drilling and proper fracturing owing to a lack of knowledge of damage factors and fracture sequences, both of which are crucial for regulating crack propagation. Conventional laboratory approaches often fail to capture the nuanced variation seen in HDR. To address this, the present work uses a three-dimensional optical approach called digital image correlation (3D-DIC) to investigate damage factors in HDR.

HDR samples from the DOE UTAH FORGE project's Well 16B (78)-32 are subjected to uniaxial (D 1.5", L 2") and diametrical (D 1.5", L 1") compression using a 100kN precision electro-mechanical load Instron frame at a constant displacement rate of 0.05mm/min. During the uniaxial and diametrical compression studies, a Trilion 3D-DIC image capturing system was used to monitor the samples at a rate of 10 frames per second in a non-contact manner. To monitor deformation during loading, a black-in-white speckle pattern is placed on the specimen. The GOM 3D-DIC system is used to process images, visualize data, and analyze HDR damage variables under various load circumstances.

The findings showed that DIC-generated quantitative full-field strain preliminary maps (tension, compression, and shear) include all sequences involved in the damage process as well as discrete strain localization zones (SLZ). Damage factors are quantified using DIC maps to assess sample damage; the tension-compression ratio ranges between 2% and 8%. The damage evolution process of HDR specimens is divided into four phases that are assessed using damage variables: initial damage stage, linear elastic, elastic-plastic, and plastic damage stage. The damage variable regulates the deterioration of the material's stiffness, resulting in a nonlinear relationship between stress and strain. The damage to the SLZ demonstrates that it is bigger than the entire. The damage was at 65% in the yield stage and 35% in the first two stages. The 3D-DIC findings showed that the sample failed when the overall damage variable reached 0.25-0.35, and the damage in the SLZ region reached 0.8-near unity.

The damage variable in HDR, which indicates fracture progression, is a unique characteristic in geothermal systems. These results have a substantial impact on our capacity to forecast the damage process in EGS. DIC outperforms CT, SEM, and AE methods in test range, cost-effectiveness, accuracy, and full-field monitoring. It improves our knowledge of damage factors in anisotropic and heterogeneous HDR, increases fracturing efficiency, and improves heat extraction from EGS.
Autonomous Drilling Fluid Management System - Expansion of Fluid Advisory System Across Multiple Fluid Systems
Authors: Abdul Razak F. , Onegova E. , Postovalov S. , Knizhnik A. , Gilad Y. , Valtysson V. , Krishnan A. , Thompson C. , Ettehadi R. , Brevik J.
Published: September 2024

This research aims to develop a Fluid Advisory System that provides recommendations for the optimal amounts of chemical additives needed to maintain desired fluid properties in various drilling fluid systems. Building on the foundation laid by the Fluid Advisory System for water-based fluids (Ettehadi et al., 2023), this project expands its scope to include both water- and oil-based muds.

To achieve this goal, a machine learning (ML) model is created to predict the target fluid properties, with separate models developed for water- and oil-based muds due to their distinct characteristics. These models utilize transfer learning techniques that allow existing models to serve as base models for similar fluid systems thereby enhancing efficiency. An integrated optimization framework determines the ideal quantities of chemical additives, ensuring precise mass calculations and optimal dilution methods.

The effectiveness of the Fluid Advisory System is validated through small-scale lab experiments which analyzed samples of water- and oil-based muds previously used offshore, despite the unknown exact compositions of these muds. The testing outcomes demonstrate the system's ability to regulate critical parameters such as mud weight, rheology, API fluid loss, pH, hardness, chloride concentration, oil-water-ratio, concentration of low gravity solids (LGS), excess lime, and electrical stability (ES).

In summary, this paper provides a detail account of the development and experimental validation of the Fluid Advisory System, which effectively manages multiple properties of drilling fluids across different fluid systems, offering substantial advantages to fluid engineers and marking a significant advancement in the drilling industry by improving accuracy and efficiency.
Production Optimization through Operate by Priority: The Development and Deployment of Downtime Advisory System to Permian Wells
Authors: Wang Yan , Kaus Joshua E. , Karantinos Emmanouil , Phi Tuan Thanh , Gast David
Published: September 2024

High-well-count Permian Basin (Permian) assets pose unique challenges in daily production operations. With hundreds of wells under the oversight of a single production engineer and a limited number of lease operators, it is very hard to accurately track a well's production uptime. In the Permian, large variances have been observed in day-to-day production volume (oil, water, gas) balances due to unrecorded downtime. Volume losses attributed to events such as liquid loading, gas lift underperformance, choking and offset frac'-hits are usually not reported. These challenges make it difficult to identify production optimization opportunities and to have confidence in allocated production datasets. This paper describes a downtime advisory system (DTAS) that utilizes data analytics and rule-based algorithms to automatically detect well production downtime. DTAS reports non-producing wells daily to the operation teams and populates a priority list with impacted volumes in order to facilitate investigation of production impacting events and ultimately achieve production uplift.

DTAS has been deployed to more than 2,500 ExxonMobil operated wells in the Permian with recommendations on daily well production downtime. DTAS identified additional production loss that was previously unrecorded, which was translated into opportunities that helped improve production optimization and allocations. The automated system has saved field personnel significant time by reducing time-on-tools and facilitating root cause diagnosis. This has enabled production engineers to focus on production uplift and achieve operational efficiency by priority.
Experimental Microfluidic Strategies for Enhanced Recovery with Ferrofluid
Authors: AlNasser Fatimah H.
Published: September 2024

The objective of this microfluidic investigation is to identify and test two novel applications for magnetic fluids in porous media for subsurface oil field applications. In particular, the study assesses the possibility of utilizing water-based or oil-based ferrofluids as agents in enhanced oil recovery and temporary in-situ valves to divert multiphase fluid flow. Ferrofluid is a liquid dispersion of nanoscale ferromagnetic particles that exhibits dynamic response to changes in magnetic fields. Three forms of external magnetic fields were tested, a stationary magnetic field from a permanent magnet, an oscillating magnetic field from an electromagnet, and a rotating magnetic field from a magnetic stirrer. The micromodel porous medium consisted of two types that are simple trapping mechanism designs (converging-diverging channel and pore doublet) and sample rock-like designs (sandstone and fractured sandstone). The experimental results confirmed that ferrofluid is an effective enhanced oil recovery agent for both the wetting and nonwetting phases and showed five different mechanisms by which ferrofluids could improve recovery at the microscale that are (i) direct displacement by the magnetic body force (ii) pore-scale agitation (iii) mobility ratio reduction by viscosity alteration (iv) interfacial tension reduction, and (v) magnetic nanoparticle chaining.
Near-Wellbore Water Imbibition Study for Cyclic Injection of CO2 into the Subsurface
Authors: Pianos M.
Published: September 2024

The present work constitutes a comprehensive study on near-wellbore water imbibition in the context of CO2 cyclic injection for storage purposes. The research, conducted at INEOS Energy and DTU Chemistry, aims to provide a deeper understanding of the imbibition process and its implications for CO2 cyclic injection practices. It uses two simulation cases, modeled in Eclipse (SLB), starting from a relatively simple Black Oil model and inductively moving to a more complex compositional one. The models are two-phase, isothermal, homogeneous, and consist of a horizontal injection well and a vertical cross-section around it. Some of the most impactful parameters of the near-wellbore water imbibition process are investigated to enhance knowledge of the industrial approach of Project Greensand. Initially, the concept of CO2 cyclic injection and its potential as a tool for reducing greenhouse gas emissions are introduced. Then there are references to the key theoretical concepts around CO2 injection and expected results based on previous studies. Numerical simulations are used to investigate the dynamics of water imbibition near the wellbore during CO2 cyclic injection. The results of these numerical models are analyzed in detail, revealing key insights into the mechanisms of water imbibition and the factors that affect its rate and extent. Continuing, the impact of various parameters, such as injection rate, saturation function hysteresis, brine salinity, and well location, on near-wellbore water imbibition is examined. The findings of this study, which show how key simulation parameters affect water imbibition, have significant implications for the optimization of CO2 cyclic injection processes, contributing to enhanced operational efficiency and sustainability in the energy industry. Overall, this work provides a valuable contribution to the field of engineering, offering a deeper understanding of the complex dynamics of near-wellbore water imbibition during CO2 cyclic injection. The insights gained from this study have the potential to inform and improve industry practices, leading to more efficient approaches to the application of a crucial decarbonization technology.
The Effect of Silicon Dioxide Nanoparticle Functionalization on the Filtration Properties of Drilling Fluid and Porous Media Permeability
Authors: Ibrahim M. A.
Published: September 2024

Near wellbore permeability alteration can hinder well productivity and injectivity performance. Drilling-induced permeability alterations frequently receive criticism because it is the first human action to disturb the formation's chemical and mechanical equilibrium. Despite various mitigating techniques, conventional overbalanced drilling with drilling fluid including colloid is still preferred because of its benefits for well control and wellbore stability. Current research trend focuses on engineering nanoparticles in drilling fluid to reduce extended fluid and solid infiltration into the formation. However, there is a fundamental knowledge gap regarding the effect of the nanoparticle surface properties on drilling fluid filtration properties. Due to the substantial difference in the surface-to-weight ratio in nano-sized materials, there is a distinct difference in the properties that govern matter at nanoscale as compared to those of the micro and macroscale. Consequently, surface properties play a more significant role for nanoparticles to work as filtration control material. Literature data suggest a relationship between nanoparticle charge and potential and drilling fluid filtration properties, albeit with limited discussion. Additionally, the effect of these properties on fluid and solid infiltration into porous media has not been studied. This research aims to study the effect of nanoparticle charge and potential on the drilling fluid filtration properties and porous media permeability. Silicon dioxide nanoparticles, functionalized with carboxyl and quaternary ammonium groups, were tested. Return permeability experiments on Berea sandstone core analyzed filtration properties and permeability alteration. The drilling fluid was water-based, and the formation fluid was sodium chloride brine. Results revealed that larger nanoparticle sizes produced a more consistent result, while smaller nanoparticles had better filtration properties but were more susceptible to change in other variables. Positively charged nanoparticles showed slightly better filtration properties but adversely affected return permeability due to strong adsorption onto sand particles. Permeability alteration was up to 89% for positively charged nanoparticles, compared to 53% for base drilling fluid, 83% for unfunctionalized nanoparticles, and 21% for negatively charged nanoparticles. This study provides insights into the significance of nanoparticle surface properties on drilling fluid filtration and transport in porous media, affecting permeability.
Optimizing CO2 Sequestration in Coal Seams: A Machine Learning Framework for Wettability Prediction
Authors: Ifenaike A. O.
Published: September 2024

In the face of escalating global climate challenges, Carbon Capture, Utilization, and Storage (CCUS) emerges as a pivotal technology in the quest to mitigate atmospheric CO2 emissions. Among the various geological formations suitable for CO2 sequestration, coal seams represent a unique and promising option, especially those that are unmineable due to depth, thickness, or other economic constraints. The success of this formation is closely tied to the intricate interactions among CO2, coal, and in-situ fluids, with wettability playing a crucial role. A deep understanding of wettability is pivotal for optimizing CO2 injection strategies and ensuring the long-term stability of the sequestered CO2. Over the past decade, researchers have increasingly turned to data-driven methods to predict rock-fluid interactions, yet the limited size of datasets has constrained the representativeness and applicability of their results. Additionally, traditional methods for assessing wettability, such as contact angle measurements, Amott test and interpolation techniques involving nuclear magnetic resonance, are costly and time-consuming.

In response to these challenges, this study employs a data-driven approach, leveraging a collection of experimental datasets to predict wettability in a coal/CO2/brine system. The framework incorporates features such as physical properties of coal, ambient conditions, CO2 characteristics, coal rank, and surface chemistry, utilizing advanced data analysis techniques such as heatmaps, cross-validation, feature engineering and importance analysis to enhance model generalizability. Four machine learning models were employed in this study: Bayesian Linear Regression, Explainable Boosting Machines (EBMs), Google's TabNet algorithm and a composite of the last two models (Voting Regressor.) The voting regressor model demonstrated superior predictability with a coefficient of determination (R2) score of 0.86, mean absolute percentage error of 5.32% and root mean squared error of 5.92 on the blind test set, outperforming the other stand-alone models. The strong correlation coefficient of 0.954 between measured and predicted wettability values underscores the model's robustness. Consequently, this study advances the predictability of key parameters for CO2 sequestration and underscores the feasibility of using coal seams for long-term CO2 storage, significantly contributing to CCUS research.
Low Salinity Water Injection Modeling by Craig-Geffen-Morse (CGM) Method: A Case Study in a Homogeneous Reservoir
Authors: Lubis Samuel Dacosta
Published: September 2024

Low Salinity Water Injection (LSWI) is widely used in the global oil industry for enhanced oil recovery (EOR) due to its operational simplicity, cost benefits, and environmental friendliness compared to other methods. However, the underlying mechanisms of LSWI are still debated, prompting the need for a more realistic model to simulate fluid displacement in reservoirs.

This study proposes the Craig-Geffen-Morse (CGM) method as an alternative approach to model low salinity waterflooding and reservoir fluid displacement. The study also investigates the impact of reservoir properties on oil recovery during low salinity water injection, considering factors such as pattern area, reservoir thickness, sand layer permeability, and fluid mobility ratio.

Using Visual Basic for Applications (VBA) codes in Microsoft Excel, the CGM method is implemented to calculate equations and correlations. The study conducts a sensitivity analysis to observe the effects of several parameters on reservoir performance.

The results show that injecting fresh water may increase oil recovery by 8.2% compared to high salinity water injection. While water salinity data is not directly considered, the study demonstrates a clear relationship between reduced water salinity and improved oil recovery based on certain reservoir property conditions. Additionally, variations in pattern area and thickness have minimal impact on reservoir performance, yielding similar oil recovery factors. Sand layer permeability only affects oil recovery when high salinity water is used, and higher fluid mobility ratios significantly reduce oil production.

The findings align with previous research, supporting the applicability and practicality of the Craig-Geffen-Morse method for modeling low salinity water injection. These findings contribute to further development in this field.
Evaluation of Dentin Tubule Occlusion Using Diode laser 976 nm and 0.5% Sodium Flouride gel using SEM: An Ex Vivo Study.
Authors: Siddig Reem Esam , Ellateef Abd Ellateef  Abbass Abd , Awooda Elhadi Moheildin
Published: September 2024

Background: Dentin hypersensitivity (DH) is a painful condition associated with challenging treatment options.
Aims: This study aimed to evaluate the effectiveness of a diode laser (976 nm) for occluding dentinal tubules in vitro and to compare the effectiveness of this laser with that of the conventional chemical agent sodium fluoride gel in occluding the Dentinal Tubules.
Materials and Methods: Ten extracted human premolars were utilized in the current in Ex vivo experimental scanning electron microscopic (SEM) study. Using a diamond saw with coronal dentin from each tooth specimen, dentin disks 1.0 mm in thickness were cut perpendicularly to the long axis of each tooth. Ten dentin disks were prepared, and each specimen was divided into four equal parts, pretreated with ethylenediaminetetraacetic acid (17%), and subsequently divided into four groups: (Group 1) the control group, (Group 2) the 976 nm diode laser with a power of 1 watt, (Group 3) the sodium fluoride only group and (Group 4) the combined laser and sodium fluoridearnish group. The samples were analysed using a scanning electron microscope at different magnifications (100 µm, 50 µm, 20 µm, and 2 µm).ANOVA was used to compare the differences in dentinal tube diameter among the four groups, with the level of significance set at a P value ˂0.05.
Results: Group 1 (control, no treatment) had all the dentinal tubules opened. Both the laser group and the sodium fluoride group demonstrated partial occlusion and narrowing of most of the dentinal tubules, while the combined group showed total occlusion of almost all of the dentinal tubules. There was a statistically significant difference between the four groups regarding the diameter of the dentinal tubules.
Conclusions: The combination of a diode laser (976 nm), 1 W, and sodium fluoride varnish significantly affected dentinal tubule occlusion, thus preventing DH.
Reproductive Health and Rheumatoid Arthritis
Authors: Ranjbaran Mohammad Erfan , kazemi Maryam
Published: September 2024

Introduction: The prevalence of Rheumatoid Arthritis (RA) has been steadily increasing over the last thirty years, particularly among women. Due to the conflicting results of various studies on the link between rheumatoid arthritis and reproductive health, we have undertaken this study to explore their relationship. Method: This cross-sectional study utilized primary data from women involved in the Fasa Persian Cohort. The study examined the frequency of RA and its association with various factors related to reproductive health, including age at first pregnancy, number of alive children, history of abortion, and infertility. SPSS software was utilized for data analysis, with the significance level set at p < 0.05. Results: 5557 women with an average age of 48.6 ± 9.5 years participated. Of these women, 7.2% were diagnosed with rheumatoid disease, with an average onset age of 38.2 ± 15.2. The study did not find a significant correlation between RA and factors such as number of pregnancies, age at first pregnancy, duration of breastfeeding and number of children. Conclusion: The study suggests that the experience of RA is independent of gynecological, obstetric factors, or reproductive life. This finding may provide reassurance to women affected by RA.
A novel QTL carrying NB-ARC family genes enhances grain protein content without grain weight penalty in wheat (Triticum aestivum L.).
Authors: Fandade Vikas , Mishra Ankita , Sharma Vinita , Kumar Prashant , Madhawan Akansha , Singh Dalwinder , Kumar Jitendra , Singh Pradeep , Das Deepak , Mantri Shrikant , Sharma Shailendra , Oak Manoj , Roy Joy
Published: September 2024

Wheat (Triticum aestivum L.) is a global food crop with low protein content of 9-12%. Enhancing grain protein content (GPC) without compromising yield is challenging largely due to the negative correlation between yield and GPC. Genome wide DNA markers, high-throughput phenotyping, genome-wide association studies (GWAS), and QTL mapping have facilitated the identification of quantitative trait loci (QTLs). This study utilized a stable recombinant inbred line F7-9 (RIL) population, genotyped via high-depth genotyping by sequencing (GBS), and conducted multi-environmental trials to identify stable QTLs for GPC. In contrast to the inverse relationship of GPC and thousand grain weight (TGW), the RIL population showed positive correlation of 0.143 (P<0.001) with TGW. The RIL population also showed significant genetic variation in GPC, with a heritability of 0.72, and identified ten QTLs for GPC on chromosomes 2B, 5B, 5A, 4B, and 1D. Among these, QGPC.nabi-2B.2 and QGPC.nabi-5B.1 were identified as major and stable QTLs. Precise mapping of QGPC.nabi-2B.2 identified NB-ARC domain-containing proteins as potential candidate genes for GPC regulation. Three SNPs from the QGPC.nabi-2B.2 region were converted to Tetra-ARMS-PCR markers. Subsequently these markers were used to validate in Indian wheat varieties and in a genetically different RIL population. This study provides a foundation for further research into the genetic regulation of GPC in wheat and suggests that NB-ARC genes could play a significant role in improving GPC, potentially enhancing wheat's nutritional quality without yield penalty.
Soil Moisture Prediction Based on Long Short-Term Memory Networks and Meteorological Data
Authors: Jiang Ping , Niu Guizhen , Li Guangming
Published: September 2024

As an important factor directly affecting the growth of crops, a reasonable and accurate prediction of soil moisture can effectively improve the quality of crop growth. The deep learning model LSTM is often used to predict soil moisture, nevertheless, the predictions generated only by LSTM exhibit a lack of accuracy. To resolve this issue, in this study, we propose a method that combines meteorological features and correlation of soil at different depths to predict soil moisture. By verifying the autocorrelation and cross-correlation of soil at different depths, it is determined that the soil moisture characteristics can be regarded as a smooth time series, and the meteorological data can be used to predict the soil moisture. Afterwards, the LSTM model was used to predict soil moisture from meteorological data, and it was found that there was a significant disparity between the actual value and the predicted value, and the accuracy of prediction was improved by reconstructing the model. To validate the proposed model, we selected moisture data from six monitoring points in unirrigated (rainfed) wheat fields in the designated areas of the Yellow and Huaihai Seas to validate the proposed model, and obtained accurate moisture prediction values, proving the validity of the model.
Determinants of Profitability in the Indian Inorganic Chemical Sector: An ARDL Empirical Analysis
Authors: Mahor Nirbhay , Banerji Amit
Published: September 2024

This research study into the impact of various factors on the profitability of India's crucial inorganic chemical industry, examining the interplay between a company's profitability and key variables such as Research and Development Intensity (RDI), net fixed asset turnover ratio, leverage, Export Intensity, and net working capital requirement. Utilizing data from the Prowess financial database spanning from 1998 to 2021, using the autoregressive distributed lag (ARDL) method, to assess both the short-term and long-term dynamics between return on assets (ROA) and these independent variables. Findings from the ARDL analysis reveals a short-term negative impact of RDI, net fixed asset turnover ratio, and leverage on ROA, whereas export intensity and net working capital requirement positively influence profitability. Over the long term, RDI continues to exert a negative effect on ROA, whereas positive impacts are observed from export intensity and net working capital requirement on profitability. The empirical investigation within the inorganic chemical sector, this study sheds light on how strategic financial management of factors such as RDI, asset turnover, leverage, export intensity, and working capital can significantly bolster a firm's financial performance, offering valuable insights for companies use to refine their strategies and enhance profitability.
Influencing factors of decision-making and lower limb motor function in speed skaters
Authors: Pang Bo , Ji Zhongqiu , Zhu Lei
Published: September 2024

Purpose Measuring and comparing the resting-state brain functional connectivity of skaters at different levels, by comparing the differences between various indicators of high-level and low-level athletes which provides theoretical reference for beginners to improve their skill level during movement practice.
Methods More than five years of high level speed skaters, low level speed skaters as the subjects, Using functional near-infrared spectroscopy (fNIRS) changes in the resting state cerebral cortex, Corresponding the spatial coordinates to the functional network, Divided into the default network (DMN), the ventral attention network (VAN), the somatomotor network (SMN) and the visual network (VN), include four functional brain networks. The knee flexion / extension moment and total work, ankle plantar flexion / dorsiflexion and valgus / varus torque and total work were tested by the isokinetic muscle strength system.
Results and conclusions (1) Long-term skating training can enhance brain executive function, promote the functional connection within and between different functional networks of the brain, mainly by the sensorimotor network. (2) Long-term skating training promotes the efficiency of the cerebral cortex, which makes the information transmission and collaborative processing of the sensorimotor network more efficient, reflecting the unique benefits of skating training. (3) Speed skating squatting practice with ankle strategy to regulate posture stability, has a positive role in improving the ankle joint plantar flexion torque, the faster the joint angle speed changes, the smaller the torque change, so the appropriate slow speed is conducive to make the torque peak.