bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Various Parameters on Petroleum Oil Removal from Produced Water with Novel Nanobubbles/microbubbles Flotation
Authors: Colic M.
Published: February 2024

Produced water at offshore and onshore petroleum and natural gas extraction sites is very complex and contains many inorganic and organic contaminants. Such contaminants include free and emulsified petroleum oils and suspended solids. Gas flotation technologies are commonly used to remove finely dispersed oil droplets and suspended solids. New generation of flotation systems use nanobubbles-microbubbles generators that can produce very small bubbles ranging from 1 - 1,000 nanometers and 1-30 microns. However, influence of various parameters such as pH, salinity, temperature, pressure, type, and dosage of polymeric flocculants, mixing energy and hydraulic residence time have not been studied. In this manuscript we present detailed analysis and literature review of parameters that influence the performance of such flotation systems. High molecular weight and high charge density cationic flocculants significantly enhance the removal of dispersed oils and solids. Dual cationic-anionic flocculant approach is particularly efficient. Centrifugal hydrocylone based flotation systems where nucleation of bubbles and flocs occur at the same time are particularly effective. Higher temperature and pH enabled better emulsion flocculation and flotation. Salinity impairs flocculant activation and the performance of flotation system.

Nanobubbles enhance flotation and flocculation at high NaCl concentrations. We propose a "hungry black hole" model for nanobubbles effects in flocculation and flotation: nanobubbles occasionally collapse and like black holes release a strong jet of gas that can then penetrate oil droplets, flocculant chain networks and floc pores. Secondary nano and microbubbles nucleation in those pores then creates large light flocs that float in seconds to the top of flotation units.
Dissolvable Materials for Buoyancy Driven Downhole Robots
Authors: Seren H. , Zeglache M. , Powell C. , StMichel N.
Published: February 2024

Dissolvable materials made a positive impact in many downhole applications by reducing down-time, cost, and operation complexity, especially as frac plugs. For a new application for these materials, here we investigate their deployment as ballasts that can be attached to buoyancy driven untethered downhole robots, such as the Sensor Ball [1]-[2]. The Sensor Ball is an untethered downhole tool that takes a ballast to sink in the well fluids and releases it to become buoyant, hence it can return to the surface. Although the ballast is released on-demand via a magnetic actuator, using a dissolvable ballast is useful for two reasons: 1) The clutter left behind is minimized; 2) Provides a fail-safe mechanism such that the buoyancy is regained even when the weight releasing system fails. The Sensor Ball needs a ballast material that is as dense as possible to easily offset its effective density. Among the readily available materials, aluminum alloys are suitable, but pose problems such as highly exothermic reaction. These materials can cause extreme heating that can raise the local temperatures over 100 °C at downhole pressures. A secondary issue is the byproduct formation and aggregation. The aggregated solids inside water cause a mud-like viscosity that can entrap the Sensor Ball. Polymer spray coatings and separation of functions for clutter prevention and fail-safe mechanisms were effective in reducing the exothermic heating and mud formation. We also investigated 3D printed dissolvable polymer containers with metal powders. Although this method was useful in addressing the heat generation problem, the containers showed mechanical integrity problems.
Sand Channel Characterization and Fault Identification Utilizing Ultra-Deep Resistivity 3D Inversion in Complex Clastic Reservoirs
Authors: Elkhamry A. , Bikchandaev Eduard , Fouda M. , Taher A.
Published: February 2024

Modifying the well position to maximize production requires both detailed reservoir characterization and mapping of sub-seismic features to identify and remain within the optimal zone. Sand channel characterization, including mapping their orientation, thickness and geometry is important to enable optimization of the well path in this complex environment to maximize the net to gross. Combining high Resolution Imaging tools used traditionally for sand channel characterization and fault identification with ultra-deep 3D electromagnetic inversion improves understanding and provides clear visualization of sand channel behavior.

Advanced azimuthal ultra-deep resistivity tools with improved signal to noise ratio and processing techniques have enabled better reservoir visualization. Resistivity and geo-signal curves, images, raw components and associated inversions are provided which can be widely used for landing, geo-steering, geo-mapping and lithology identification (Anisotropy) or even petrophysical analysis (Far Field Saturation) at distance. Recent advances provide 3D Inversions, which can be used for sand channel characterization (mapping out the orientation, thickness, and geometry) and fault identification (dip, strike and amplitude) with confidence. In the candidate wells, 3D EM Inversion revealed sand channels distribution in the area for the target reservoir.

An innovative workflow for Sand channel characterization and fault identification with ultra-deep resistivity 3D inversion in complex clastics reservoirs has been developed based on the acquired 3D Inversion data and combining multiple sources of data from near wellbore as well as offset logs. In the first field case two sand channels were identified, in the second field case a break with displacement (fault) dislocating the reservoir has been identified and characterized with dip, strike and amplitude values from the 3D Inversion. The 3D Inversion and proposed workflow could be used for optimizing current and future well placement by adjusting well azimuth while drilling, planning sidetracks and field studies incorporating the 3D data into seismic models.

This paper demonstrates field cases utilizing ultra-deep resistivity 3D inversion for mapping out the orientation, thickness and geometry of the sand channels and fault identification in complex clastic reservoir to provide increased reservoir understanding.
Data-Driven Drilling Performance Improvement: The Synergy of Digitalization and Offset Well Data Utilization
Authors: Elghoneimy Mahmoud , Hiep Nguyen , Fakhrylgayanov Ayrat , Gari Abdulrahman , Nsanov Nurbol , Osman Ahmed , Chen Wei , Gonzalez Luis F , Shatrovskiy Anton
Published: February 2024

Data-driven optimization for drilling operations is becoming increasingly important in the oil and gas industry. Digitalization and utilization of historical offset well data can provide critical insights into improving drilling performance and aid in making informed decisions for the best selection of drilling parameters. This paper aims to present an integrated approach between a research center and the field that leverages offset well data and drilling engineering domain knowledge with data science and machine-learning models to improve drilling performance through more stable drilling dynamics. This novel drilling optimization method utilizes a digitalized process that combines drilling dynamics data from offset wells and drilling engineering domain knowledge with advanced data science algorithms (statistical analysis, optimal searching, and machine learning) to generate optimum drilling parameters automatically. This hybrid optimization approach, integrating science and domain knowledge, aims to systematically minimize the energy dissipated in drilling shocks and vibration (S&V), which would then lead to maximizing drilling efficiency in a continuous improvement cycle. The effectiveness of this approach is proven through case studies from various oil and gas fields in which we discuss the associated key challenges for current and future developments. The authors showcase through these examples the significant gains in drilling engineering efficiency when automated data analytics’ workflows are used to make the utmost value of offset well data utilization in improving drilling parameters. The results include a significant reduction of S&V, which leads to better directional drilling accuracy and reduced downhole tool failure risks. The approach has also increased drilling performance, resulting in faster and more efficient drilling operations. Furthermore, the use of this approach has led to a reduction in overall drilling time, resulting in substantial cost savings for drilling major oil and gas fields.
Acquiring Real-Time Data in Under Balanced Coiled Tubing Drilling for Geosteering: The Current Success and Factors Limiting Physics Boundaries
Authors: Ibrahim Mohd Azizi , Enezi Faisal Naif , Alnasser Fatimah Mohammed
Published: February 2024

The objective of this article is to share the current success of real-time logging while drilling (LWD) data acquisition in under balanced coiled tubing drilling (UBCTD) that enables petrophysical evaluation and precise depth control in identifying layers targeted for geosteering a well. In addition, the paper will generally discuss the trial results of technologies tested in UBCTD operations, the success and limiting factors. A future outlook to acquire more advanced logging technology to assist a precise geosteering are discussed later as challenges for further development in UBCTD

The method of tool testing procedure and analysis of the acquired data addressed the then current tools potential and, in some cases, directed the research towards the improvements required before the tool is operationally viable for further testing. The tools trials were conducted in multiple environments from controlled to simulation of the actual UBCTD conditions. In most of the cases, an ideal environment was created to acquire the desired data in order to prove the viability of the concept. The data acquired from the trial runs are treated carefully to avoid missing information and overlooking of the hidden potentials. UBCTD conditions challenged the current LWD tool physics especially for porosity measurements due to a couple of factors, such as the borehole size and the multiphase condition of fluids used in the process.

With the aim of assisting geosteering in complex environments, multiple conceptual tools were tested in UBCTD in attempt to acquire LWD data. The tested LWD tools are GR, Acoustic and Resistivity where the trial was simulated in a real coiled tubing drilling environment. Such tools consist of a set of devices dedicated to obtain certain measurements, these are developed for Gas/Water velocity measurement; electrical/resistant probes for water holdup and optical probes for gas holdup; and pulsed neutron. The aforementioned tools were tested in controlled environments to prove the concepts. There were mixed results indicating that there are real challenges associated with developing LWD for UBCTD

The value of sharing these trial tests is to ensure the concepts and practicality for developing a logging tool are captured before proceeding to tools manufacturing. Some concepts are mere theories therefore require further enhancements to be viable before the actual LWD tools were built. Sharing such information could help the industry to focus on certain critical aspects in developing super slim LWD tool in the ever-growing UBCTD operation in future.
Diagenesis of Platform Carbonates Flanking the Tazoult Salt Wall (High Atlas, Morocco)
Authors: Travé A. , Chaves A. , Moragas M. , Baqués V. , Martín-Martín J. D. , Saura E. , Cofrade G. , Cruset D. , Munoz-Lopez D. , Cantarero I. , Playà E. , Carola E. , Vergés J.
Published: February 2024

The Central High Atlas of Morocco is a double verging major diapiric province encompassing SW-NE trending salt-related ridges and Lower to Middle Jurassic deposits over synclines (minibasins) in between them. Typically, Pliensbachian and Bajocian platform carbonates flanking diapirs exhibit partial dolomitization in the vicinity of the diapir wall. The interpretation of the diagenetic products and diagenetic evolution of these dolomitized carbonates may be complex due to different fracture patterns, brecciation, fluid pathways, heterogeneities, localized uplift associated with diapiric activity, among others. The present work focuses on the dolomitization affecting Late Aalenian-Bajocian platform carbonates flanking the Tazoult salt wall, localized in the center of the Central High Atlas. Analytical work includes standard microscopy, cathodoluminescence and 𝛅13C–𝛅18O isotopic analyses. A paragenetic sequence is discussed to reconstruct the diagenetic evolution of the flanking platform carbonates. The results highlight the major influence of diapirism and igneous intrusions on the fluid circulation. Moreover, the present work complements a previous work related to the Liassic successions flanking the Tazoult salt wall.
Designing Matrix Acidizing Treatments with Particulate Diverters—Part I: Model and Predictions
Authors: Tardy Philippe M. J. , Ziauddin Murtaza , Vidma Konstantin , Khan Abdul Muqtadir
Published: February 2024

While particulates are often used in the field to optimize reservoir coverage by diverting the injected treatment fluids into lower injectivity zones, the optimal job design may be difficult to reach without the proper models. In our study, we detail models for particulates transport, bridging, plugging, diversion and degradation, which are the tools required to provide reservoir and completion specific design guidelines for various scenarios. Each model is built using dedicated experimental procedures. Experimental data are presented together with their correlations.

The efficiency of particulate fluids depends on multiple factors including the magnitude of the injectivity contrast present in the reservoir, how much flow resistance may be achieved by accumulating particulate filter cakes in perforations and how quickly the accumulation can start. The onset of diversion requires perforation plugging and, potentially before that, perforation bridging. The onset of bridging depends on parameters such as particulate loading, rate through perforations, and size of perforations and of particulates. Once the cake forms, diversion may start depending on the permeability of the cake, the permeability of the zone connected to the plugged perforation, and the perforation type. Particulate and cake degradation rate is also an important aspect to consider. This paper elaborates on the models relevant to quantify diversion efficiency of particulate-based fluids in the field. The paper also provides new and useful insights on the important factors that should be considered during the design phase.
Testing the Robustness of Quadruped Robots for Unmanned Inspection Activities in the Energy Industry
Authors: Pencelli Manuel , Bonacchi Luigi Bono , Fiorucci Marta , Schillaci Guido , Youssef Ali , Politano Andrea , Bettini Alessandro , Porciani Daniele , Salusti Lorenzo , Cioncolini Stefano , De Magistris Giovanni
Published: February 2024

The energy industry is witnessing a growing interest in adopting robotic technologies for unmanned operations, such as asset inspection. Robots performing inspection tasks are safer, cost-effective and can help minimize risks, especially when assets are in extreme environments. Although different studies highlight the positive impact that the adoption of robots may have in the energy industry, there is little evidence of the robustness of such tools during operation. This is mostly due to the limited access for the scientific community to operational sites and corporate data, and to the limited availability of robust robotic platforms certified to - and thus allowed to - operate under specific conditions. This study aims at filling this literature gap by testing one of the few robot platforms available in the market that are well-suited for the energy industry, as they can be released with an ATEX certification (ATmospheres Explosibles) for operation in environments with explosive atmospheres.

This paper tests the robustness of a quadruped robot in autonomous inspection activities on a mineral lube oil console used to lubricate gas turbines and available at the Baker Hughes site in Florence (Italy). A qualitative analysis of robot performances in critical tasks for mission accomplishment - such as locomotion, step climbing, visual inspection, recharge, and docking - has been conducted and discussed.
Innovative Non-Conventional LCM Solution for Total Losses across Fractured Formations
Authors: Olivares Tulio , Al-Zahrani Walid , Al-Dossary Fahad
Published: February 2024

Curing total losses of drilling fluids in fractured formations is one of the most challenging fluid loss scenarios to control. Loss zones are unpredictable due to large vugular zones, extended and connected fracture structures formations. However, based on proper evaluation of the offset wells data, losses events can be anticipated to customize a Lost Circulation Material (LCM) solution. Non-Conventional LCM solutions typically are used to go beyond and be more aggressive, aiming to cure the losses, reduce non-productive time and resume programmed operations. We worked to locally develop an Innovative Non-Conventional LCM solution, which involves pill trains combinations to cure the losses across fractured formations. After successful lab testing verification, those formulations were implemented at the field with satisfactory results.

Well A was identified with total losses across fractured formation. Previously lab tested Non-Conventional LCM solution was recommended. At Well A location, the first pill was made with blend of organic polymers with super absorbent materials, specifically designed to impart viscosity and swell as it fills the fractures. producing a viscous slurry designed to flow into downhole loss zones, where it will swell and seal large fractures providing a base for the second pill pumped to rapidly de-water, leaving behind a drillable plug. The second pill pumped consisted on a blend of sealants which form a stable, high solids, high fluid loss LCM slurry. Upon contact with a thief zone, this second pill will rapidly de-water, leaving behind a drillable plug-in fracture, voids and vugular spaces across the loss zone. A soft squeeze was hold for several hours. The resulted plug was easy drilled through without the danger of unintentional sidetracking. As conclusion, we were able to customize an Innovative Non-Conventional LCM solution to regain the circulation on well A, allowing them to continue with the programmed operations and eliminating non-productive time in this well.

This paper discusses how this innovative customized Non-Conventional LCM Solution was designed, lab and field tested with successful results curing total losses scenarios across fractured formations, resulting in considerable non-productive time mitigation while drilling across losses zones.
Automated Estimation of Mechanical Specific Energy as a Tool for Stratigraphic Interpretation During Real-Time Drilling Operations
Authors: Peña-Gutiérrez John , Sabirov Airat
Published: February 2024

Limitations in volume and quality of geological and geophysical data result in challenges for lithostratigraphic interpretation in shallow sections of many development wells. Correct interpretation of key formation tops is critical for the recognition of casing points and for the early identification of geological units that imply drilling hazards. This study describes how Mechanical Specific Energy (MSE) curves can be used as a complementary tool for lithostratigraphic interpretation where petrophysical logs and rock descriptions are not available, particularly in shallow well sections. This work shows that MSE delivers high resolution curves that represent changes in drilling conditions and mechanical rock properties (often associated with lithostratigraphic markers). Lastly, this MSE driven lithostratigraphic interpretation method was successfully employed in a highly variable and complex stratigraphic succession of clastic, carbonate and evaporitic sedimentary rock succession.
Development and Application of an Annular Electronically-Controlled Packer
Authors: Yang Qinghai , Hou Ze , Jia Weite , Qu Jingxue , Wu JiLei , Wu Xi
Published: February 2024

Electric control packers have the characteristics of simple and fast setting and unlocking processes, and are commonly used for short-term testing operations that require reservoir sealing. At present, electrically controlled packers are generally driven by electric hydraulic pressure, which has disadvantages such as complex structure, low reliability, and no large diameter liquid passage, and cannot meet the needs of rapid underground operations. This article proposes and develops a fully electrically controlled annular packer, which is driven by an annular motor with a driving torque of 8N. m. After being amplified by a reducer, the driving force of the rubber cylinder can reach 6KN. The packer has a 25mm center liquid passage, which can meet the needs of high-flow liquid flow; In order to improve reliability and avoid downhole accidents that cannot be unsealed, the innovative design of four protection mechanisms, including magnetic coupling torque transmission, rubber cylinder stroke position monitoring and limit protection, motor driven current limit protection, and forced unsealing structure, has greatly improved the reliability of the packer. This packer has been successfully applied in the stratified sampling and testing operations of PetroChina Jilin Oilfield, achieving rapid sealing of underground reservoirs. The packer adopts a modular design concept and has the ability to pass through cables. It can be combined with other electronic control tools to meet the layered sealing requirements of other layered process measures and has good application prospects.
Intelligent Optimization of Drilling Parameters Based on Multiple Drilling Agents
Authors: Pei Zhijun , Song Xianzhi , Hu Zhijian , Pan Tao
Published: February 2024

Drilling parameter optimization is one of the important ways to improve drilling efficiency and reduce drilling cost. Multi objective intelligent optimization technology has the characteristics of comprehensive consideration of factors and fast solution speed, and is suitable for drilling parameter optimization scenarios. Based on the drilling data of a vertical well in Tarim Oilfield, the rate of penetration (ROP) prediction agent, pipe string friction calculation agent and bottom hole cleanliness agent are established by using artificial intelligence or mechanism methods. Based on non-dominated sorting genetic algorithm II(NSGA-II), several established drilling agents are combined, and intelligent optimization model of drilling parameters is established. The evaluation function of the drilling scheme is set up to select the optimal drilling parameter optimization scheme from numerous Pareto solutions under the condition of ensuring operation safety, and the scheme is applied and verified in this well for Kangcun Formation and Jidik Formation with low ROP. According to the optimization results of drilling parameters, under the condition of ensuring the bottom hole cleaning and normal drilling, compared with the previous drilling plan, the ROP of Kangcun formation is increased from 3.43m/h to 7.72m/h; The ROP of Jidik formation is increased from 4.76m/h to 8.84m/h. The ROP of the two formations has been increased by 125.1% and 85.7% respectively, which can shorten the drilling cycle and reduce the drilling cost to a certain extent.
Case Study of Appraisal Well to Unlock STOIIP in High Pressure, High H2S Environment
Authors: Mahrooqi Alkhattab , Siyabi Rashid , Hinai Nasser , Balushi Hamid , Hadhrami Abdullah
Published: February 2024

This case study demonstrates the value of appraisal well in high pressure/ H2S stringers in the south of Oman. The appraisal objective is to narrow down the high uncertainty in ODT, Structure and reservoir properties to unlock the full STOIIP of the field. A comprehensive and integrated evaluation of different data, such as production data, pressure data and high uncertainties triggered the need to appraise the field. Planning and execution of appraisal well was associated with many challenges and risks. However, the integration between different disciplines led to a safe delivery of the well. The results of the new appraisal well unlocked 7% STOIIP that confirmed the MBAL STOIIP scenario of having higher volumes. The outcome of the appraisal well opened an area for adding two extra oil producers. Additionally, the appraisal results triggered the need of reprocessing the seismic data to reduce structural uncertainty and hence better estimating the in-place volume.
At-The-Bit Look-Around 3D Inversion; Key Milestone Achieved with Innovative Close to the Bit Ultra-Deep Azimuthal Resistivity Sensors
Authors: Elkhamry A. , Maimani A. Al , Fouda M. , Taher A.
Published: February 2024

Efficient well placement profoundly depends on early geo-steering decisions to maximize reservoir contact. In highly undulated thin target zones, this can be more concerning as the formation dip changes abruptly. Such environments present a significant challenge where geo-mapping instruments are placed farther behind the bit in the bottom hole assembly, leading to relatively late decision making and more aggressive well path corrections. This paper presents the advantages of placing geo-mapping tools close to the drilling bit position leading to enhanced reservoir contact (Net-to-Gross) and less tortuous well bores.

Deep and ultra-deep azimuthal resistivity measurements have historically provided a step change for proactive geo-steering, yet the challenge has always been the proximity of the sensors to the bit opposed to other less sophisticated near bit sensors. Well placement with conventional configurations have been regularly utilized to ensure maximum reservoir exposure with varying results due to unforeseen geo-structural changes such as the formation dipping regime (1D environment), lateral boundaries (2D environment) or channels (3D environment). A new tool design was introduced in which the ultra-deep resistivity transmitter was embedded into the rotary steerable system allowing 1D and 3D inversions to be closest to the bit position, offering at-the-bit visualization of the reservoir, hence, earlier, and less aggressive well path corrections could be made to optimize well placement and increase reservoir contact. Geo-mapping formation boundaries while drilling high angle sections with a near bit ultra-deep azimuthal resistivity inversion minimized potential reservoir exits while also minimizing wellbore tortuosity. This is critical for efficient well placement, minimizing drilling risks and smooth completions deployment. Horizontal wells were placed in thin reservoir targets that are successfully resolved by integrating 1D and 3D inversions to improve reservoir mapping, remote lithology and fluid identification to optimize well placement and reservoir evaluation. The accuracy of reservoir visualization from the near-bit resistivity inversion has been validated by other logging while drilling measurements in the drill string, such as triple combo and azimuthal images from several sensors.

This paper presents the global first at-the-bit look-around inversion utilizing an ultra-deep resistivity sensor embedded in a rotary steerable system for horizontal well placement in two target sand packages. The proximity of the ultra-deep sensor to the bit enabled quicker decisions to optimally place the well in the target zone while reducing well tortuosity leading to a higher net-to-gross and a smoother well trajectory. This also facilitated the deployment of the completion equipment saving costly rig time.
Continuous Bottomhole Pressure Estimation Using Machine Learning and Physics-Based Methods – A Field Case Study
Authors: Zalavadia H. , Sabharwal V. , Sankaran S.
Published: February 2024

Bottomhole pressure (BHP) has been increasingly integrated into modern workflows in characterizing subsurface reservoir, evaluating well production performance, and optimizing artificial lift designs for unconventional reservoirs. The increasing need for agile asset development planning demands robust and continuous well performance evaluation, for which bottomhole pressure lays the foundation. However, there are several challenges that most of the unconventional operators are facing. It is uneconomical to install permanent downhole pressure gauges and have continuous measurement throughout the entire life span on all wells across the entire asset. A practical approach is to estimate BHP from wellhead pressure by using physics-based multi-phase flow correlations. However, since various multi-phase flow correlations were developed with limited field datasets and assumptions only applicable for certain flow conditions, these empirical or mechanistic models are not generalized to fully characterize the fluid flow behaviors that are applicable for various flow patterns without constant manual selection and tuning. Finally, there is a need for robust estimation of BHP with various changing wellbore configurations under different artificial lift designs and types through the life of the well.

In this work, we propose a hybrid methodology integrating physics-based and machine learning models to provide BHP with high accuracy. Five different candidate multi-phase flow correlations were selected for physics-based models to estimate BHP from routine daily production data and consider any change of artificial lift designs and types. With the availability of some downhole pressure gauges to calibrate BHP estimates, we propose to improve BHP estimation in two major steps – first, selecting the best physics correlation for each producing day based on dynamic criteria using a classification method and second, improving the physics-based BHP estimate using a physics-informed machine learning (PIML) approach.

The machine learning models were trained based on historical downhole gauge pressure data and validated with data hold-out in history and data measured. The results of model performance showed that this hybrid pre-trained model can be leveraged as a ‘virtual downhole gauge’ to continuously provide high-accuracy BHP estimation in a robust and consistent manner in the absence of physical downhole gauges.

In this paper, we present a field case study to demonstrate the deployment and usage of continuous BHP estimation integrating physics-based and machine learning models. This framework has been successfully deployed for one of the largest U.S. unconventional shale basins with over 3000 producing wells. By leveraging this hybrid methodology, high-accuracy and continuous BHP estimates can be provided at field or asset level to streamline well performance analytics workflows for unconventional reservoirs and facilitate better asset development decision-making.
Rotating Equipment Switchover Optimization to Reduce Emissions and Enhance Equipment Reliability
Authors: Gohel K.
Published: February 2024

The association of rotating equipment switchover strategy with machinery health and reliability is discussed. The paper includes the design considerations for spare equipment in processing facilities, need for a switchover strategy, factors affecting the equipment switchover and the benefits of optimizing the switchover strategy in terms of equipment reliability and HSE.
Purification of Produced Water from Kuwaiti Oil Fields Using Ceramic Membranes
Authors: Salem F. Al , Thiemann T. , Kawamura K. , Nakamura A. , Poulose V. , Saibi H.
Published: February 2024

Fresh water resources are increasingly becoming scarce, which is a concerning matter due to the rapid growth in global human population, industrialization and pollution of fresh water sources and underground aquifers. Therefore, utilizing water treatment technologies in water intense processes such as oil and gas production and increasing the industries’ water efficiency have become ever so important. Produced water (PW) from oilfields is the largest waste stream in the oil and gas industry, and the quantities of PW globally has been recorded at more than 250 million barrels per day. The purification of this large amount of by-product by means of ceramic membrane filtration has been investigated in this study with samples from an oilfield in the State of Kuwait with a reservoir containing mostly heavy oil and a high H2S content. The sampled PW originates from an oilfield with approximately 80 percent water cut. PW has a number of components that cause production problems such as scaling and corrosion. Therefore, the treatment of PW before its disposal or reuse is seen to be urgent. Discharging this water to the environment can also lead to severe environmental impact. Therefore, rigorous regulatory standards have been implemented for the disposal of PW into the environment, which are a significant challenge to the oil and gas industry. The understanding of the characteristics and the treatment of PW can avoid the degradation of production facilities and equipment and consequently lower the maintenance costs at the production sites. In this study, the PW samples were filtered using a φ30/100mmL ceramic membrane element with a nominal pore size of 0.1μm.
Effect of Acidizing Additives on the Corrosion Rate of Retarded HCl Recipes
Authors: Almulhim N. , Almoajil A.
Published: February 2024

Retarded HCl acid treatment has been used as an effective method for enhancing hydrocarbons production from carbonate reservoirs by creating highly conductive channels. A thorough understanding of performance of the retarded HCl additives is essential to prevent or minimize incompatibility of acidizing additives in the treatment. The objective of this work is to highlight the effect of retarded HCl recipe additives (e.g. H2S scavenger) on corrosion rate and compare it to regular HCl recipes. The paper additionally discuss typical testing conducted with carbonate acidizing acid recipes to assess performance.

HCl acid and inorganic/organic acid retarded agents were obtained for this study. Typical experimental testing were conducted to assess acid recipes includes (1) thermal compatibility up to 300°F to identify precipitation or sludge formation, (2) iron control testing to assess the capacity of the acid to keep iron in solution at pH of 4 up to 300°F, and (3) coreflood and CT scan testing to assess wormhole formation profile and precipitation. XRD, TGA, ESEM, and NMR experiments were conducted to analyze solids and precipitation. An autoclave reactor was used to conduct corrosion testing to assess the effect of acid recipe additives on the corrosion rate up to 300°F.

The effect of acid additives on the corrosion rate of 15 wt% retarded HCl acid with divalent salt and chemical retarder was investigated. It has been observed that the use of H2S scavenger with the retarded acid recipes resulted in significant increase in corrosion rate from 0.05 to 0.10 lb/ft2. The corrosion testing results indicated the EDTA-based chelating agent slightly increased the corrosion rate of the retarded acid recipe. However, the significant increase in corrosion rate was due to the presence of H2S scavenger and large amount of MgCl2 in the HCl recipe. H2S scavenger can be used in this retarded acid recipe. Alternatively, during acidizing operation of H2S scavenger pill can be used as spacers before and the pumping of the retarded acid.
Carbon Dioxide Induced Organic Rich Shale Maturation: A Dual Benefit of Carbon Dioxide Sequestration and Hydrocarbon Production Enhancement
Authors: Moh-Ali A. E. , Hassan A. M. , Mahmoud M. A. , El-Husseiny A. H. , Abu-Mahfouz I. S.
Published: February 2024

Organic-rich shales have gained significant importance as an abundant source of natural gas and oil. Kerogen maturation can be induced by altering the temperature and pressure conditions over time. This study explores the effects of carbon dioxide injection on kerogen maturation in unconventional shale resources, examining its effects on petrophysical, geochemical parameters, and hydrocarbon productivity. Three types of organic-rich unconventional shales were used to study the effects of artificial maturation. Artificial maturation, aided by CO2, significantly reduced total organic content by (10-40%) and improved rock porosity and permeability due to microfractures induced. The study found significant increases in free hydrocarbon volume (S1) and potentially produced hydrocarbons (S2) in different samples, with slight changes in other geochemical parameters like hydrogen index and sulfur content.

Ultimately, this study proposes a method for improving the potential for oil and gas production through kerogen maturation. Using CO2 as an inducement for the maturation of organic-rich shale has shown promising results in accelerating the process while also having the potential to sequester CO2 due to its high affinity for adsorption in shale formations. Furthermore, the use of CO2 as an inducement could lead to more efficient hydrocarbon recovery compared to common maturation processes, as it enhances shale gas production by increasing kerogen thermal cracking.
Oil Pipeline Leak Detection Using Deep Learning: A Review on POC Implementation
Authors: Al Azri Ahmed , Al kaabi Sultan , Al Zakwani Saud , AL Sulaiman Mohammed , AL-Mawali Afifa
Published: February 2024

Oil and gas production operations are key sources of environmental pollution which exposing the people and effect the human activity in the world. Petroleum Development Oman (PDO) is the leading exploration and production oil and gas companies in the Sultanate of Oman which lead to avoid adverse health effects in Oman. Oil leaking detecting in a timely that leaking could be undetected for long time. However, the precise methods could help improving the oil leaking detecting response process in channel required resources with more effectively to be concerned regions. Existing Synthetic-aperture radar (SAR) approaches are limited by their algorithm complexity which difficult to work with imbalanced data sets, doubts to select optimal features, and the relatively slow detection. Using deep learning approach could speed up the oil detection. convolutional neural network U-Net segmentation models based on oil leaking detection could be achieve promising automated results. However, there are insufficient features extraction due to loss of target to detect oil leaking or shadows in drone images that commonly appear in various size ,shapes and brightness levels, which the images that captured under many conditions. To overcome all these limitations, we improved deep learning model named Pyramid Scene Parsing Network (PSP Net). The proposed algorithm can probabilistically detect when and where a leak is taking place and can segment from shadow noise images at the frequency of data collection. Thus, PDO Oman could reduce millions of Dollars when direct action from operators that received a quick true alarm of oil leaking. The effectiveness of the proposed algorithm is demonstrated through A proof of concept (POC) based on a realistic dataset that collected history data that our deep learning algorithms achieved the perfect predict the oil leaking before occurs.
Advances in KHI Technology for Sour Systems and Environmental Acceptable Properties
Authors: Jackson S. J. , Jardine J. , Leontieff A.
Published: February 2024

Kinetic Hydrate Inhibitor (KHI) evaluation in wet sour gas has been extensively publicized showing H2S can, in some cases, have an adverse effect on a KHI. Advances in technology has overcome this for Type I and II systems where subcooling can be high. Development of an environmentally acceptable KHI with comparable performance that is not affected by continuous corrosion inhibitor, and compatible in high saline, elevated temperature systems bring further opportunities for KHI globally.
Síndrome metabólica: seus riscos e malefícios para a saúde
Authors: Silva Daniel Rodrigues , Arantes Maria Clara Rodrigues , Dutra João Pedro Cabral , Silva Douglas Roberto Guimarães , Pereira Larissa Mirelle de Oliveira
Published: February 2024

Objetivo: Compreender as melhores condutas e formas de intervenção utilizadas na síndrome metabólica para promover a melhoria da qualidade de vida desses pacientes. Métodos: O presente trabalho se trata de uma revisão integrativa, descritiva de abordagem qualitativa. Em relação aos critérios de inclusão estabelecidos para os trabalhos, foram escolhidos os estudos que foram publicados, preferencialmente, entre 2017 e 2023 e foram selecionadas 10 pesquisas. Resultados: Foi possível observar que as principais manifestações clínicas são a obesidade central e a insuficiência à insulina; os principais riscos estão diretamente associados com alguma manifestação clínica, sendo, principalmente, relacionadas com à obesidade, levando ao aumento de doenças cardiovasculares e diabetes. Considerações finais: Os riscos e malefícios estão associados aos sintomas apresentados. Como principal sintoma de risco, foi citada a obesidade, que acarreta em diversos problemas na saúde do indivíduo que não só de ordem metabólica, mas também como a diabetes, doenças cardiovasculares, entre outras, podendo causar a morte da pessoa. Verificou-se que os tratamentos mais eficazes para a melhoria da qualidade de vida dos indivíduos que sofrem com a Síndrome Metabólica são a uma dieta equilibrada e a prática de exercícios físicos.
A Cross-Sectional Study of Etiology and Clinico-Hematological Profile of Pancytopenia in Children at Tertiary Care Centre in Western India
Authors: Kale Anjali , Idhate Tushar , Reddy Rishivardhan
Published: February 2024

Objectives

Pancytopenia is one of the most common blood disorders observed in routine clinical practice. There are few studies analyzing pancytopenia in Indian scenarios. This cross-sectional study is aimed to identify the cause of pancytopenia and analyze the clinico-hematological characteristics of children with pancytopenia in Western India. So this study was conducted to evaluate clinico-hematological profile of children presenting with pancytopenia and to determine the etiology of pancytopenia in Western India.

Material and Methods

This two-year descriptive cross-sectional study was conducted in a tertiary care referral hospital. All children with pancytopenia, ranging in age from 1 month to 18 years, were enrolled in the study. A thorough history was taken, as well as general and systemic examination findings, hematological parameters, and bone marrow examination findings were recorded.

Results

The age group of enrolled patients ranged from 1 month to 18 years in the 130 cases evaluated (63 males and 67 females), while the mean age was 9.8 years. Fever was the most prevalent symptom (n = 111, 85.40%), followed by generalized weakness and weight loss. Pallor was the most common physical manifestation, followed by knuckle pigmentation, hepatomegaly, and splenomegaly. Study results concluded that the most common cause of pancytopenia was megaloblastic anemia, followed by acute leukemia, aplastic anemia, and infections. Megaloblastic anemia can be distinguished from other causes of pancytopenia based on dietary habits, hematological parameters and serum B12 levels, potentially obviating the necessity for a bone marrow test in most pancytopenia patients.

Conclusion

In pancytopenia patients, detailed initial hematological investigations, including bone marrow examination, are beneficial for correct diagnosis. Although megaloblastic anemia is the most prevalent cause, other factors to examine include aplastic anemia, leukemia, Hemophagocytic Lymphohistiocytosis (HLH), hypersplenism, Systemic Lupus Erythematosus (SLE), and viral infections. When a complete history, clinical examination, and baseline hematological parameters are adequately assessed, bone marrow examination can be avoided in most pancytopenia patients.
Reducing Over-indebtedness through Shariah Compliant Crowdbuying
Authors: Ghaouri Mohamed Hamza , Hmaittane Abdelmajid , Kassim Salina
Published: February 2024

Households’ over-indebtedness has various social and economic consequences. With an increasing number of over-indebted households and rising individual bankruptcies, especially in the post-COVID-19 pandemic era, the efficiency of the solutions available to target this issue is becoming questionable. The purpose of this study is to propose an innovative Shariah-compliant mechanism based on crowd-buying, aiming at alleviating households’ over-indebtedness. The present study adopts a qualitative research design based on an extensive review of the existing literature and a case study of the Real Estate Crowdbuying (REC) model. The study also presents a Shariah assessment of the REC model. The study found that the REC model has five contradictions with the guidelines of Shariah and proposes an enhanced version based on Shariah compliant contracts. As per the authors’ knowledge, this is the first study that provides a Shariah assessment to the REC model and proposes an enhanced Shariah-compliant version. The main limitation of this research is the limited focus on the Shariah compliance of the model. Further studies might explore the regulatory challenges of the application of this model in Malaysia and other Muslim countries. The proposition made by this paper contributes to broadening the range of Shariah-compliant instruments aiming at alleviating households’ over-indebtedness and curbing individual bankruptcy rates.
Functionalised Al(III) metal organic frameworks for fluorescence sensing of nitroaromatic vapours
Authors: Haj-Yahya Amina , Kouskouki Dimitra , Margellou Antigoni G. , Andreou Evangelos K. , Armatas Gerasimos S. , Lazarides Theodore
Published: February 2024

The employment of fluorescence sensors provides a platform for rapid and efficient in-field detection of nitroaromatic compounds and is gaining increasing reserach ground. Herein, we report the synthesis and characterisation of three new fluorescent Al(ΙΙΙ) MOFs, structurally analogous to MIL–53, with the assigned formula {Al(OH)(bdc)1-n(L–1)n}·xsolv (bdc2- = terephthalate; L–1 = 2–((benzyl)amino)-terephthalate). L–1 is a strongly fluorescent dicarboxylic ligand with a pendant π–electron rich aromatic group suitable for electron transfer processes towards electron–deficient nitroaromatic guests. Our MOFs show strong fluorescence quenching upon exposure to vapours of nitrobenzene, 1,3-dinitrobenzene, 4-nitrotoluene, 2,4-dinitrotoluene. Additionally, we prepare and study MOF-polymer composites in the form of thin films that are strongly quenched in the presence of nitrobenzene vapours.
Computational Investigation on Adsorption and Activation of Atmospheric Pollutants CO, NO and SO on Small Cobalt Clusters
Authors: Shabeeb Muhammad , Maity Surajit
Published: February 2024

The adsorption of CO, NO and SO on cobalt clusters (Co2-7) were investigated using density functional theory. The adsorption energy supports efficient chemisorption of greenhouse gases on the cobalt clusters, with CO and NO forming one to three Co-C and Co-N bonds, respectively, the first being the most stable. The SO formed bidentate complexes with Co-S and Co-O bonds in ConSO structures, displaying notably high adsorption energy. The interactions between Con clusters and gas molecules (G) result in weakened bonds of CO, NO, and SO, evident through increased bond lengths, red-shifted frequencies, and lowered local vibrational force constants in ConG complexes. The results with Bond weakening and charge transfer from metal to gas molecules suggest strong catalytic potential for small cobalt clusters in activating gas molecules. The current research findings hold significance in the quest for efficient catalytic processes to capture and recycle gaseous pollutants, contributing to a sustainable future.