bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prospective Risk Factors of Toxoplasmosis Seropositivity in Pregnant Women: The Fundamental Role of Community Healthcare Education
Authors: Eltayeb Lienda , Hamad Nasir , Babiker Abeer 
Published: December 2021

Background: The present study conducted a survey on awareness of toxoplasmosis infection, with an emphasis on risk factors, and an assessment of toxoplasmosis prevalence in pregnant women in Al-Kharj province of KSA.	Methods and Results: A cross-sectional study with a qualitative approach was carried out from August 2018 to February 2019. The study recruited all pregnant women who attended maternity and children’s outpatient clinics. The non-probability sampling approach was used to select 345 blood samples from study subjects. T. gondii-specific IgG and IgM antibodies were identified using ELISA. Each participant enrolled in the study was provided with a validated questionnaire to fill out by an assistant of the laboratory technician or an antenatal care nurse. In addition to socio-demographic data, simple closed-ended questions about established risk factors for T. gondii exposure were included in the questionnaire items, and answers were listed in a three-point Likert scale (agree, disagree, I am not sure). The overall prevalence of T. gondii-specific antibodies among study subjects was 12.75%; 29(8.40%) women were positive for IgG only, 9(2.6%) - for IgM, and 6(1.7%) - for both IgG and IgM antibodies.	About 41.4% of participants were in the first trimester of pregnancy; among them 31(9%) were positive for T. gondii antibodies. 82.8% of pregnant women had chronic infection in the first trimester, while 44.4% of those women also had an acute infection. The number of respondents to the questionnaire was 345 participants with a response rate of about 100%. It is important to note that 81.5% of women were unaware that toxoplasmosis is dangerous, and two-thirds of them didn't know the dangerous complications for the fetus and newborn.	Conclusion: The current study concludes that there is a low prevalence of toxoplasmosis among Saudi pregnant women in Al-Kharj province. A general program must be implemented to increase population awareness, especially among the at-risk populations.
Evaluating Phase Blockages and Mobility Changes During Pressure Transient Analysis
Authors: Bellabiod Sofiane , Karacali Ozgur , Aris Abdelkader , Deghmoum Abdelhakim , Theuveny Bertrand 
Published: December 2021

Abstract
Pressure transient analysis (PTA) is a cogent methodology to evaluate dynamics of hydrocarbon reservoirs. Numerous analytical and numerical models have been developed to model various types of wellbore, reservoir, and boundary responses. However, the near-wellbore region remains to be perplexing in pressure transient analysis. In this paper we investigate the pressure transient behavior of phase blocking and mobility variations caused by fluid phase interactions or properties, such as viscous drag forces and surface tension at the near-wellbore region and their impact on pressure transient evaluation.
We have used real field examples to scrutinize relative effects of mobility variations in pressure transients. The impact of capillary number (Nc) acting on the near-wellbore region and its influence on pressure transient behavior and skin alteration were examined in detail. Several real field examples honoring actual reservoir rock special core analysis (SCAL) and fluid pressure/volume/temperature (PVT) properties have been studied. Actual field data discussed in this paper for PTA were captured during drill stem testing (DST) operations from various hydrocarbon reservoirs in the Berkine Basin of Algeria. PVT laboratory-measurement-based fluid properties were used in conjunction with tuned equation of state (EOS) models to ensure consistency between wells and reservoirs.
Pressure transient analysis of a gas condensate reservoir system can depict various mobility regions, especially while flowing below dew point pressure. In some cases, three-distinct-mobility regions can be identified as: a far-field zone with initial gas and condensate saturation; a mid-field zone with increased condensate saturation and lower gas relative permeability; and a near-wellbore zone with high Nc which increases gas relative permeability and mobility. These three-distinct-mobility regions form due to condensate dropping out and fluid interactions in the near wellbore. We demonstrate, with real-life field examples of the near-wellbore region, how the relative effects of viscous drag forces and surface tension forces acting across the liquid and gas interface can enable the reference fluid phase to regain its mobility. We further investigate the evaluation of skin factor in such circumstances and show how the existence of phase blocking and velocity stripping can cause over-estimation or under-estimation of skin factor.
We present a novel set of real field examples and relations between various zones in hydrocarbon reservoirs to avoid snags of misleading pressure transient interpretations and how composite models can be accurately used to represent complex cases. Field examples from Algerian hydrocarbon reservoirs are depicted. The findings could be easily applied for similar reservoirs in other parts of the globe to identify and model such intricate systems.
Well Integrity Leak Diagnostic Using Fiber-Optic Distributed Temperature Sensing and Production Logging
Authors: Abeling Joerg , Bartels Ulrich , Singh Kamaljeet , Dutta Shaktim , Agrawal Gaurav , Kumar Apoorva 
Published: December 2021

Abstract
Fiber optics has many applications in the oil and gas industry. In recent years, fiber optics has found usefulness in leak detection. The leaks can be efficiently identified using fiber-optic distributed temperature sensing measurement, thereby mitigating the health, safety, and environmental (HSE) risk associated with well integrity. Further, a production log can be used to gain more insight and finalize a way ahead to resolve well integrity issues.
An innovative solution-driven approach was defined, with fiber-optic distributed measurement playing a key role. Multiple leaks were suspected in the well completion, and a fiber-optic cable was run to identify possible areas of the leak path. After the fiber-optic data acquisition, a production log was recorded across selective depths to provide an insight on leak paths. After identifying leak depths, a definitive decision between tubular patching and production system overhaul was decided based on combined outputs of the fiber-optic acquisition and production log.
Results are presented for a well where multiple leaks were successfully identified using the novel operational approach. Further, operational time was reduced from 3 days (conventional slickline memory or e-line logging performed during daylight operation) to 1 day (a combination of fiber-optic distributed temperature sensing and production log in a single run). The diagnosis of production system issues was completed in one shut-in and one flowing condition, thereby reducing the risk of HSE exposure with multiple flowing conditions (to simulate the leak while the conventional production logging tool is moved to different depths in the well). Additional insight on leak quantification was confirmed from the production log data, where one leak was noted at the tubing collar while the other leak was noted a few meters above the tubing collar. This observation was substantial in deciding whether to proceed with tubing patch or replace the entire production tubing.
The novel operational approach affirms fiber-optic distributed temperature measurement's versatility in solving critical issues of operation time and reducing HSE exposure while delivering decisive information on production system issues. The paper serves as a staging area for other applications of similar nature to unlock even wider horizons for distributed temperature sensing measurement.
Informed Decisions Guided by GeoMechanics to Improve Drilling Performance: A Case Study from Onshore Field, Abu Dhabi; UAE
Authors: Benmamar Salim , AL Arfi Saif Al Arfi , Perumalla Satya , Salem Gamal , Baruno Agung , Saha Sankhajit , Bhatt Pranjal 
Published: December 2021

Abstract
ADNOC (Abu Dhabi National Oil Company) recently drilled some wells in Onshore Abu Dhabi (Field-A) and encountered consistent hole instability from Umm Er Radhuma (UER) to Simsima. Thus, a GeoMechanical review was proposed to investigate the root causes, if any, and recommend possible remedies for the upcoming drilling campaign.
While detailed drilling event analysis allowed to investigate the correlation between the mud weight program and well trajectory, borehole image log analysis and geological understanding from nearby fields indicated the possible role of structural and lithological features on hole instability. Integration of drilling engineering data and regional geological knowledge helped to narrow down the possible causes of drilling challenges. Sedimentalogical review of Image logs have established some correlation between rock types and hole instability events.
Drilling experience shows there is very narrow margin for loss and/or gain to occur. There is regional geological evidence of the presence of a wide range of vuggy structures, as well as natural fractures and/or faults. These features tend to make Simsima formation heterogeneous in terms of permeability and more prone to losses. Since most fractures are parallel to SHmax direction and well was drilled towards Shmin direction, there are greater chances of encountering faults and/or fractures, which would be critically-stressed and lead to loss and/or gain situations. Geomechanical parameters helped highlight the magnitudes and orientations of principal stresses. Observations of several tight hole and stuck pipe events while tripping from Radhuma and UERB shale to Simsima seem to indicate mud weight used was insufficient. Role of multiple failure mechanisms was identified, and relevant solutions were recommended as well as implemented to achieve the drilling success.
The case study presented here emphasizes how different carbonate textures and the presence and orientation of natural fractures and/or faults within Simsima formation can impact hole instability with respect to wellbore trajectory. Proactive implementation of recommendations from this analysis on well planning and fluid design resulted in improvement of drilling performance and reduction of non-productive time in new wells.
Utilizing NMR Workflow to Optimize Power Water Injector Placement in the Presence of Tar Barriers
Authors: Hursan Gabor , Sahhaf Mohammed , Amairi Wala’a 
Published: December 2021

Abstract
The objective of this work is to optimize the placement of horizontal power water injector (PWI) wells in stratified heterogeneous carbonate reservoir with tar barriers. The key to successful reservoir navigation is a reliable real-time petrophysical analysis that resolves rock quality variations and differentiates tar barriers from lighter hydrocarbon intervals. An integrated workflow has been generated based on logging-while drilling (LWD) triple combo and Nuclear Magnetic Resonance (NMR) logging data for fluid identification, tar characterization and permeability prediction.
The workflow has three steps; it starts with the determination of total porosity using density and neutron logs, the calculation of water-filled porosity from resistivity measurements and an additional partitioning of porosity into bound and free fluid volumes using the NMR data. Second, the total and water-filled porosity, the NMR bound fluid and NMR total porosity are used as inputs in a hydrocarbon compositional and viscosity analysis of hydrocarbon-bearing zones for the recognition of tar-bearing and lighter hydrocarbon intervals. Third, in the lighter hydrocarbon intervals, NMR logs are further analyzed using a multi-cutoff spectral analysis to identify microporous and macroporous zones and to calculate the NMR mobility index. The ideal geosteering targets are highly macroporous rocks containing no heavy hydrocarbons. In horizontal wells, the method is validated using formation pressure while drilling (FPWD) measurements.
The procedure has been utilized in several wells. The original well path of the first injector was planned to maintain a safe distance above an anticipated tar-bearing zone. Utilizing the new real-time viscosity evaluation, the well was steered closer to the tar zone several feet below the original plan, setting an improved well placement protocol for subsequent injectors. In the water- or lighter hydrocarbon-bearing zones, spectral analysis of NMR logs clearly accentuated micro- and macroporous carbonate intervals. The correlation between pore size and rock quality has been corroborated by FPWD mobility measurements. In one well, an extremely slow NMR relaxation may indicate wettability alteration in a macroporous interval.
An integrated real-time evaluation of porosity, fluid saturation, hydrocarbon viscosity and pore size has enhanced well placement in a heterogeneous carbonate formation where tar barriers are also present. The approach increased well performance and substantially improved reservoir understanding.
A Novel Corrosion Monitoring and Prediction System Utilizing Advanced Artificial Intelligence
Authors: Katterbauer Klemens , Dokhon Waleed , Aulia Fahmi , Fahmi Mohanad 
Published: December 2021

Abstract
Corrosion in pipes is a major challenge for the oil and gas industry as the metal loss of the pipe, as well as solid buildup in the pipe, may lead to an impediment of flow assurance or may lead to hindering well performance. Therefore, managing well integrity by stringent monitoring and predicting corrosion of the well is quintessential for maximizing the productive life of the wells and minimizing the risk of well control issues, which subsequently minimizing cost related to corrosion log allocation and workovers.
We present a novel supervised learning method for a corrosion monitoring and prediction system in real time. The system analyzes in real time various parameters of major causes of corrosion such as salt water, hydrogen sulfide, CO2, well age, fluid rate, metal losses, and other parameters. The data are preprocessed with a filter to remove outliers and inconsistencies in the data. The filter cross-correlates the various parameters to determine the input weights for the deep learning classification techniques. The wells are classified in terms of their need for a workover, then by the framework based on the data, utilizing a two-dimensional segmentation approach for the severity as well as risk for each well.
The framework was trialed on a probabilistically determined large dataset of a group of wells with an assumed metal loss. The framework was first trained on the training dataset, and then subsequently evaluated on a different test well set. The training results were robust with a strong ability to estimate metal losses and corrosion classification. Segmentation on the test wells outlined strong segmentation capabilities, while facing challenges in the segmentation when the quantified risk for a well is medium.
The novel framework presents a data-driven approach to the fast and efficient characterization of wells as potential candidates for corrosion logs and workover. The framework can be easily expanded with new well data for improving classification.
Geology-Driven EUR Forecasting in Unconventional Fields
Authors: Temizel Cenk , Canbaz Celal Hakan , Alsaheib Hasanain , Yanidis Kirill , Balaji Karthik , Alsulaiman Nouf , Basri Mustafa , Jama Nayif 
Published: December 2021

Abstract
EUR (Estimated Ultimate Recovery) forecasting in unconventional fields has been a tough process sourced by its physics involved in the production mechanism of such systems which makes it hard to model or forecast. Machine learning (ML) based EUR prediction becomes very challenging because of the operational issues and the quality of the data in historical production. Geology-driven EUR forecasting, once established, offers EUR forecasting solutions that is not affected by operational issues such as shut-ins. This study illustrates the overall methodology in intelligent fields with real-time data flow and model update that enables optimization of well placement in addition to EUR forecasting for individual wells.
A synthetic but realistic model which demonstrates the physics is utilized to generate input data for training the ML model where the spatially-distributed geological parameters including but not limited to porosity, permeability, saturation have been used to describe the production values and ultimately the EUR. The completion is given where the formation characteristics vary in the field that lead to location-dependent production performance leading to well placement optimization based on EUR forecasting from the geological parameters. The algorithm not only predicts the EUR of an individual well and makes decision for the optimum well locations. As the training model includes data of interfering wells, the model is capable of capturing the pattern in the well interference.
Even though a synthetic but realistic reservoir model is constructed to generate the data for the aim of assisting the ML model, in practice, it is not an easy task to (1) obtain the input parameters to build a robust reservoir simulation model and (2) understanding and modeling of physics of fluid flow and production in unconventionals is a complex and time-consuming task to build real models. Thus, data-driven approaches like this help to speed up reservoir management and development decisions with reasonable approximations compared to numerical models and solutions. Application of machine learning in intelligent fields is also explained where the models are dynamically-updated and trained with the new data.
Geology-driven EUR forecasting has been applied and relatively-new in the industry. In. this study, we are extending it to optimize well placement in intelligent fields in unconventionals beyond other existing studies in the literature.
Outside the Box: Innovative Application of Diversion as a Replacement for Bridge Plug
Authors: Chang Hong , Yi De Qiang , Lv Yang , Zhao Ming , Cao Peng Liang , Zhang Lin , Hou Rui , Di Yi Liang , Chen Jie , Zhang Lu , Li Hao Yan , Fu Yun Long , Liu Yuan , Wang Wei Kan 
Published: December 2021

Abstract
Effective stage-to-stage isolation is typically accomplished by setting a bridge plug in a properly cemented casing between stages. This isolation plays a vital role in a horizontal well multistage fracturing completion. Failure of isolation not only impacts the well productivity but also wastes fracturing materials.
The challenges isolation failure poses for stimulation effectiveness include both detection and remediation. First, there has been historically no reliable and cost-effective solution to detect stage-to-stage isolation onsite. One may only start to realize this problem when inconsistent production is observed. Second, existing remedial actions are seldom satisfying in case of an isolation failure. Most commonly, a new plug is set to replace the failed one. However, because the perforation clusters of an unstimulated stage may create irregularities in well inside diameter (ID) (e.g., casing deformation or burr), there is a risk that the plug will be damaged or become stuck when it passes the perforation area. Also, when the plug passes a perforation cluster, the perforations start to take in the pump-down fluid, which can increase the difficulty of the pump-down job.
A novel remedial action uses high-frequency pressure monitoring (HFPM) and diversion to solve both challenges. The stage isolation integrity is evaluated in quasi-real time by analyzing the water hammer after the pump shutdown. In the case of a plug failure, large-particle fracture diversion materials and techniques can establish temporary wellbore isolation through a quick and simple delivery process. To close the cycle, the effect of the diversion can be evaluated by HFPM, which can reveal the fluid entry point of the treatment fluid after diversion.
The technique was applied to two cases in Ordos basin in which wellbore isolation failure interrupted the operation. The problem identification, development of the solution workflow, and observation from treatment analysis are discussed. In both cases, the stage-to-stage isolation was recovered, and the drilled sand body was successfully stimulated without involving costly and time-consuming well intervention. The stimulation operation of the entire well was successfully resumed in a timely manner.
Identification of Micro Fractures in Cretaceous Bioclastic Limestone in Iraq and Its Influence on Development of Reservoirs
Authors: Wang Genjiu , Hu Dandan , Li Qianyao 
Published: December 2021

Abstract
It is generally believed that Cretaceous bioclastic limestone in Mesopotamia basin in central and southern Iraq is a typical porous reservoir with weak fracture development. Therefore, previous studies on the fracture of this kind of reservoir are rare. As a common seepage channel in carbonate rock, fracture has an important influence on single well productivity and waterflooding development of carbonate reservoir.
Based on seismic, core and production data, this study analyzes the development characteristics of fractures from various aspects, and discusses the influence of fractures on water injection development of reservoirs. Through special processing of seismic data, it is found that there are a lot of micro fractures in Cretaceous bioclastic limestone reservoir. Most of these micro fractures are filled fractures without conductivity under the original reservoir conditions. However, with the further development of the reservoir, the reservoir pressure, oil-water movement, water injection and other conditions have changed, resulting in the original reservoir conditions of micro fractures with conductivity. The water cut of many production wells in the high part of reservoir rises sharply. In order to describe the three-dimensional spatial distribution of fractures, the core data is used to verify the seismic fracture distribution data volume. After the verification effect is satisfied, the three-dimensional fracture data volume is transformed into the geological model to establish the permeability field including fracture characteristics.
The results of numerical simulation show that water mainly flows into the reservoir through high angle micro fractures. Fractures are identified by seismic and fracture model is established to effectively recognize the influence of micro fractures on water injection development in reservoir development process, which provides important guidance for oilfield development of Cretaceous bioclastic limestone reservoir in the central and southern Iraq fields.