bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-Time Sand Detection for Gas Wells Using AI Applications
Authors: Maharramli A. , Taghiyev F. , Alkhasli Sh. , Mammadov T. , Yusifov I. , Javadzade R. , Ahmadov Kh. 
Published: May 2024

Abstract
This paper proposes a novel approach for real-time sand detection in gas wells using an Autoencoder and a rule-based model ensemble. Accurate identification and early detection of sand in gas wells are crucial for effective sand management. However, the dynamic flow conditions and high-pressure environments of gas wells make sand detection challenging. The study aims to develop a methodology for sand production detection, considering the limitations of surface facilities and laboratory measurements. Methodology is based on essential features such as Acoustic Sand Detector (ASD) readings, Downhole Pressure, and Production Choke measurements. The methodology was applied for both top-side installed ASDs as well as subsea wells. To overcome the complexity of sand production patterns, we employ an Autoencoder, a deep learning technique capable of addressing the issue. In conjunction, we develop a rule-based model that leverages domain expertise to detect simpler sand patterns. The combination of these models forms a comprehensive and robust sand detection framework for real-time operations and monitoring. The proposed model demonstrates high accuracy in sand detection. After running the model on unsupervised data, we manually evaluated the results by inspecting AI estimated sand labels individually. Labels were assigned to classify them as true positives (captured sands) or false positives (false alarms). Accuracy and precision metrics were then calculated. For the top-side gas wells, the model achieves accuracy ranging from 98.5% to 100%. Meanwhile, for the subsea wells, the model achieves accuracy ranging from 89.4% to 100%. The performance of our approach demonstrates its effectiveness in detecting sand based on recordings both from surface and subsea gas wells. By accurately identifying sand presence, the proposed approach contributes to enhancing sand management strategies in the gas industry. The findings enable proactive maintenance, reduction in equipment damage, and optimization of production processes, ultimately enhancing operational efficiency in gas wells. The algorithm has been successfully deployed for a gas field located in the Caspian Basin. This paper introduces a comprehensive and robust sand detection framework that effectively addresses the complexity of sand production patterns in gas wells. By integrating the Autoencoder with a rule-based model that utilizes domain expertise, creating the framework that demonstrates high accuracy in detecting sand in both topside and subsea wells. This innovative methodology significantly enhances operational efficiency in sand management within the petroleum industry. The findings of this study make a valuable contribution to the literature, offering a novel approach to sand detection that promises to benefit the industry at large.
Unlocking Carbon Capture & Sequestration in Ultra Deep Saline Aquifers in the Western Desert of Egypt
Authors: Eleoni M. , Dredge J. , De Boer Y. , Mansour K. , Ismail A. , ElSayed R. , Merghany I. , Ellamey C. , Agam A. , Taqey A. , Gomes R. , Stojic S. , Nasiri A. , Bouchet F. , Nasreldin G. 
Published: May 2024

Abstract
Conventional subsurface reservoir candidates for CO2 Sequestration are usually just deeper than 800 m to ensure CO2 is injected at supercritical state, typically these are shallow, gently dipped, low pressure saline aquifer or completely depleted and abandoned hydrocarbon reservoirs. However, in this study within the western desert of Egypt, none of the reservoirs are abandoned and the saline aquifers below 800 m are too tight with no injectivity. So, the only way was to target ultra deep saline aquifer deeper than 3 km with virgin pressure of more than 5000 psi. These ultra deep aquifers are usually highly titled, surrounded by major faults, and highly saline and those factors act against the typical trapping mechanisms for CO2 sequestration such as structural trapping, residual trapping and CO2 solubility. In this case study, we present a novel approach that relies on innovative technology to solve this unconventional challenge to sequester 0.5 Mton CO2 per annum in ultra deep saline aquifers and open the pathway for carbon storage in unconventional storage sites.
The applied approach is divided into three phases. Phase one is site screening to automatically identify the best possible sites for CO2 storage based on a scientific scorecard. Then in Phase two, dynamic simulation of the injected supercritical CO2 plume movement within the formations while honoring advanced trapping mechanisms such as CO2 trapping due to residual trapping and dissolution in saline water. Then the dynamic reservoir simulation models are fully coupled to 3D geomechanics models to study the impact of the injection on the well integrity, cap rock integrity as well as fault reactivation and integrity. Finally in Phase 3, an economical surface facility configuration and pipelining scenarios that fit the subsurface sites’ requirements.
It was concluded through an ensemble of geological scenarios that safe CO2 trapping mechanism can be increased by 30% using a time and rate managed sequential injection scheme starting from the bottom of the formation and upwards. the dynamic simulation results show that this technique helps increasing the contact area with the saline water while leveraging high pressure to overcome low solubility in highly saline water and creating convective water density currents, hence increasing CO2 solubility in water as well as residual trapping of CO2 even in structurally marginal sites.
The followed scientific approach unlocked the potential for CO2 sequestration in ultra deep saline aquifers within the western desert to be deployed for a long-term and safe sequestration of CO2 while accounting for the complex subsurface structure to pave the way for future successful CCS projects in similar environments.
Enhancing Rigless Intervention Efficiency in Bi-Lateral Oil Producer Through Coiled Tubing Optical Telemetry, Multilateral Tool, and Single-Phase Retarded Inorganic Acid: A Case Study
Authors: Al-Mutairi F. , Slama H. , Al-Dhafiri S. J. , Al-Dwaish M. , Al-Mutawa M. , Sanyal S. , Al-Ayyaf E. , Al-Bader A. , Alajmi A. , Al-Otaibi A. , Al-Najim A. , Badrawy K. , Molero N. , Sunagatov R. , Ujagar U. , Sebaih M. Adel , Ayyad H. 
Published: May 2024

Abstract
Developments in horizontal drilling and completion techniques have enabled drilling an increasing number of wells. In the pursuit of cost optimization and enhanced recovery through maximized reservoir contact, operators are placing special interest on multilateral completions. However, multilateral wells add complexity to Rigless intervention and production enhancement work as those activities are heavily dependent on lateral accessibility.
An advanced Rigless intervention in a multilateral well relied on coiled tubing (CT) equipped with optical fiber and real-time downhole measurements and a multilateral entry tool (MLT). Downhole readings included casing collar locator (CCL), gamma ray, CT internal pressure, annulus pressure, annulus temperature, and axial force. Optical telemetry was used for lateral identification and for optimal actuation of the orienting and bent sub-components of the MLT while profiling and accessing the lateral. Throughout the stimulation treatment, optical telemetry was instrumental to understanding changing downhole conditions and keeping injection rates below fracturing pressure.
The candidate well was a carbonate bi-lateral oil producer completed through 6 1/8-in. uncased horizontal sections with both laterals having an average length of 2,400 ft. Because of real-time optical telemetry, profiling of the lateral was completed in less than 3 hours, which represents 50% reduction of the average profiling time in similar wells. Both laterals were stimulated via CT with a total of 4,000 bbl of single-phase retarded inorganic acid system (SPRIAS), which enables carbonate stimulation with better worm holing performance than emulsified acid while eliminating its drawbacks, such as high CT friction pressure and potential emulsion issues. In comparison with emulsified acid, the pumping time with SPRIAS was 35% lower, bringing additional efficiency to the intervention. The ability to make fast, informed decisions based on optical telemetry was the cornerstone of this intervention approach.
This paper documents a value case study for CT Rigless intervention for a field in the region divided between Kingdom of Saudi Arabia and Kuwait, where the combination of an array of technologies, such as CT optical telemetry, MLT, and SPRIAS, enhanced Rigless intervention efficiency, reducing total operation time by 30%, when compared to conventional CT stimulation approach in multilateral wells.
Enhancing Well Integrity and Efficiency: Deploying the 7-Inch Annulus Casing Packer (ACP) Tieback System for 9-5/8" Casing Remedial & Gas Lifting Completion Purpose in Field a, UAE
Authors: Busaeedi A. Al , Sinaga A. , El-Mahdy M. , Husein M. , El-Sayed I. , Fatima B. , Hossam H. , Amr F. 
Published: May 2024

Abstract
The deployment of the 7-inch Annulus Casing Packer (ACP) Tieback system in Field A's 9-5/8-inch casing remedial and gas lifting completion operations yields significant advantages. With its ISO 149998 V0 qualification, the ACP surpasses conventional Tieback methods, reducing the operation timeline by 5-7 days. This is achieved by incorporating design features such as cement passage ports, a V0 rated packer, and a Landing Collar with a non-shearable ball seat. The inclusion of a non-shearable ball seat obviates the need for a Bridge Plug or Acid Soluble Cement to isolate the open hole or perforation below the top of the liner, thereby eliminating the risk of cement slumping or falling into the reservoir instead of filling the annulus between the 9-5/8-inch casing and 7-inch Tieback. This enhancement not only strengthens well integrity but also leads to significant time and cost savings, representing a promising advancement in wellbore completion techniques.
Our approach revolves around the implementation of the 7-inch Annulus Casing Packer (ACP) Tieback system with a cost-effective slurry design. The assessment of long-term well integrity necessitates the use of a stress simulation tool. Tieback casing and cementing represent remedial techniques designed to cover damaged intermediate casing above the top of an existing production liner or open hole. Furthermore, they adhere to company standards, especially when the Gas Lift Mandrel is required. Tieback installation and cementing under such conditions involve important distinctions and additional risks. The use of washes and spacers ahead of cement slurries is crucial to prevent cement contamination and mixing with the fluid in the wellbore, a critical consideration due to the potential incompatibility with the completion fluid or brine. Proper evaluation of the outer casing's condition is imperative. Applying safety factors to determine the outer casing burst pressure, selecting TOC, displacing fluid, cement density and rheology, accordingly, are essential steps to lower the maximum surface pressure.
Drawing from the success of implementing this approach in 8 wells in Field A, it has significantly reduced operation timelines by 5-7 days, obviating the need for acid-soluble plugs or bridge plugs. The cost-effective slurry design, combined with stress simulation that optimizes well longevity by simulating pressure and temperature cycling during the well's lifespan, enhances wellbore integrity.
This paper represents a novel solution for enhancing wellbore completion efficiency and integrity. As well as contribution in suitability initiative by reducing operation time 5-7 days. Practicing engineers can benefit from this advancement by streamlining their operations and achieving improved outcomes while reducing costs.
Application of Machine Learning and Deep Learning to Predict Production Rate of Sucker Rod Pump Wells
Authors: Thabet S. A. , Zidan H. A. , Elhadidy A. A. , Helmy A. G. , Yehia T. A. , Elnaggar H. , Elshiekh M. 
Published: May 2024

Abstract
Sucker rod pump (SRP) systems must be designed, optimized, and operated with the aid of production data. This work seeks to create machine learning-driven models that can forecast fluid flow rate at the surface of SRP artificially lifted wells because traditional separators and multiphase flowmeters (MPFMs) may not be available in all wells. Nine machine learning models were developed using real data from 598 wells over three years, with 8,372 data points randomly split into 80% (6,697 data points) for training and 20% (1,675 data points) for testing. These models include Gradient Boosting, AdaBoost, Random Forest, Support Vector Machines (SVMs), Tree, K-Nearest Neighbor (KNN), Linear Regression, Neural Network, and Stochastic Gradient Descent (SGD). Each data set contained readings for the parameters that are easily accessible during any SRP well lifting process, including wellhead flowing pressure, casing pressure, inferred bottom hole fluid production rate, inferred bottom hole oil production rate, net liquid above pump, pump size, stroke length, pump running speed (SPM), pump depth, temperature at pump depth, oil gravity, water viscosity, and pump clearance. The performance of machine learning models is evaluated using two methods (K-fold cross-validation and repeated random sampling), and the results of the top five models (Gradient Boosting, Random Forest, AdaBoost, Linear Regression, Random Forest, and stochastic gradient descent) show that the mean absolute percent error (MAPE) between the predicted fluid rate at the surface and the actual measurements is 3.6, 3.4, 3.4, 4, and 4.4%, respectively. The correlation coefficients (R2) are also 0.937, 0.935, 0.934, 0.921, and 0.915, respectively. Additionally, an oil well in Egypt's Western Desert had its fluid flow rate at the surface predicted using machine learning models. The outcomes were contrasted with the data from the separator test itself. The actual fluid rate and the model's predictions were in perfect accord. Within a wide range of pumping circumstances and completion configurations, the machine learning models are helpful for forecasting the production rates of particular wells. This should make it possible to continuously monitor, optimize, and analyze the performance of SRP wells and to respond more quickly to operational problems. The application of the proposed machine learning models is easy, quick, and affordable when compared to conventional separators and multiphase flowmeters (MPFMs).
Experimental Investigation and Molecular Dynamics of the Fluid-Fluid Interactions Between Binary Surfactant Systems for EOR
Authors: Bello Ayomikun , Rodionov Alexander , Ivanova Anastasia , Cheremisin Alexey 
Published: May 2024

Abstract
This work aims to explore the properties and interactions between binary surfactant systems. We employed a methodology comprising experimental analysis, mathematical modeling, and molecular dynamics simulations. In the experimental study, we examined eight individual surfactants and six binary surfactant systems at various ratios to determine their critical micelle concentrations (CMCs), using reservoir oil and performing experiments at reservoir conditions. Then, Rubingh's Regular Solution Theory (RST) was applied to evaluate interactions within the binary surfactant mixtures. Finally, using molecular dynamics simulations, we characterized the microscopic interactions to comprehend how hydrophilic and hydrophobic parts of the surfactants interact with surrounding media, and how they self-assemble into aggregates such as micelles or bilayers. The key findings of our work showed that the occurrence of synergism or antagonism in lowering the CMC of binary surfactant mixtures depend on both the concentration of the individual surfactant and the type of surfactant used. Nevertheless, we noted a prevalent synergistic phenomenon in all binary surfactant systems, notably influenced by the concentration of the non-ionic surfactant. Increased concentrations of non-ionic surfactants notably enhanced synergistic interactions, fostering lowered CMC values when combined with anionic, cationic, and zwitterionic surfactants. On the other hand, an excessive concentration of cationic surfactants demonstrated relatively ‘weak’ synergistic effects, attributed to their comparatively smaller hydrophobic tail. Moreover, the formation of mixed micelles in binary surfactant systems led to a more negative free energy of micellization, thereby achieving synergistic effects between surfactants and resulting in lower CMC values. This emphasizes the crucial role of surfactant concentration in achieving synergistic outcomes within mixed systems. Generally, binary surfactant systems demonstrated lower CMC values compared to single surfactants, suggesting the potential for their use at lower concentrations to achieve desired interfacial and recovery outcomes, thereby reducing operational costs.
Optimization of Safety Height of Casing Shoe in Salt Cavern Gas Storage: A Case Study of Pingdingshan, China
Authors: Li Xiaolan , Feng Yongcun , Gu Chenwang , Li Xiaorong , Wang Guangyu 
Published: May 2024

Abstract
Salt cavern gas storage typically involves frequent multi-cycle injection and production, resulting in cyclic loading of the salt cavern system. The casing shoe, as one of the most vulnerable components, exhibits fatigue failure under cyclic loading, posing the risk of engineering accidents, including bond failure between the cement sheath and the formation, salt cavern collapse, and gas leakage. However, there has been limited research on the design of casing shoe heights for salt cavern gas storage. Therefore, in this paper, the casing-cement sheath-strata assembly was determined based on the Drucker-Prager criterion. The stability analysis of salt caverns under different interlayer distributions was conducted, and the distribution characteristics of plastic damage zones in salt caverns under different interlayer position distributions were compared. Considering the feasibility and stability of the salt cavern, the optimal range of the height of the casing shoe that meets the safety sealing requirements, the plastic zones and other indicators is proposed. The results of this paper are as follows (1) (1) Under unclamped conditions, the degree of influence of the stress concentration zone decreases as the height of the casing shoe increases. (2) When the interlayer is located above the casing shoe, the reservoir Von Mises stress becomes obviously smaller as the distance between the interlayer and the casing shoe increases. At the same time, the high strain region at the contact between the wellbore and the top of the cavity also decreases significantly, and the surrounding rock displacement at the casing shoe decreases most obviously. (3) When the interlayer is located below the casing shoe, the average value of surrounding rock displacement at the casing shoe is small, and the stress concentration area of the gas reservoir is insensitive to changes in the distribution of the interlayer. Therefore, in engineering practice, it is recommended to establish the casing shoe above the interlayer, which is more conducive to the stability of the gas storage reservoir. However, it should be noted that when the number of interlayers below the casing shoe increases, the surrounding rock displacement at the casing shoe will increase substantially, so it is recommended to have only a single interlayer below the casing shoe as much as possible. (4) No matter where the interlayer is distributed, the point of contact between the open well section and the cavity is the point of maximum equivalent stress, and there is a layer of 0.18~0.25m thick stress concentration zone on the inner side wall of the open well section. In order to avoid the local damage of the open well section leading to tensile damage at the casing shoe, the casing shoe height should be kept high enough to form a safety buffer zone. It is recommended that the casing shoe height be greater than 10m.
A New Approach to Investigate Rock Salt Creep Behavior Under Triaxial Stress
Authors: Ju Yingtong , Chen Mian , Lu Yunhu 
Published: May 2024

Abstract
Generally speaking, the rock formation with creep capability, where rocks undergo continuous deformation under constant stress, are commonly encountered especially in geomechanics, petroleum engineering, and mining science. This phenomenon significantly impacts the stability of underground engineering structures, such as petroleum/geothermal wellbores or the safety of coal mine tunnels. Therefore, investigating formation with viscous property, characterizing its creep behavior, and determining creep parameters are crucial for ensuring safe construction and production. Currently, the study of creep properties primarily relies on laboratory tests. However, rock samples obtained from underground may undergo changes in their physical and chemical properties during coring operation, transportation, and storage processes, potentially introducing discrepancies between the parameters acquired in lab and the actual value. Nowadays, apparatus capable of conducting creep or rock mechanic experiments are typically characterized by large overall dimensions, causing multiple challenges including disassembly, relocation, and poor environmental adaptability. As a result, they are typically restrained to usage in specialized laboratories. To address these limitations, this study employed a self-designed and fabricated true triaxial visualization rock mechanics test apparatus, characterized by rapid assembly, simple operation, compacting structure, etc. This apparatus allows for creep tests under true triaxial stress with only a single hydraulic power source. Moreover, even in unfavorable conditions, image acquisition can be accomplished using a phone camera, whose application has been verified through tests. Therefore, it is highly suitable for field applications in oilfields. Using this apparatus, a variety of creep experiments under different stress levels were conducted. The true triaxial visualization approach proved to be more direct in observing the influence of rock anisotropy/heterogeneity on rock creep. Through a single experiment, we were able to directly obtain creep patterns for different components, significantly enhancing experimental efficiency.