bluuebunny/crossref_metadata_2025_split huggingface dataset:
Setting New Milestones for Coiled Tubing Intervention in Mega-Reach Wells
Authors: Wheatley Edward Jason , Correia Gladwin , Adi Samhar , Molero Nestor , Silva Cremilton , Galvan Irma , McClelland Garry , French Andrew , Bragaw Thomas 
Published: October 2021

Abstract
Maximizing reservoir contact through extended-reach and mega-reach wells has become a prevalent field development strategy for major offshore operators in the Middle East. This is especially true for the giant oilfield "A", where drilling targets go beyond 40,000 ft. measured depth (MD), with MD/TVD ratios in excess of 4.5:1. Such challenging horizons call for a detailed re-evaluation of well interventions.
In 2019, the well surveillance program in the field A required intervention in a mega-reach well with a MD over 35,500 ft. and 4.5:1 MD/TVD ratio. This reach was unthinkable only a few years ago but has been made possible thanks to several recent key technological advancements, such as coiled tubing (CT) equipped with optical fiber and new CT hydraulic tractors, proactive and detailed planning during the drilling phase, the development of highly engineered CT string designs, surface equipment upgrades, and accurate software modeling.
The target well is an oil producer with horizontal section beyond 23,000 ft., completed with 6 5/8-in. pre-perforated liner and 23 swellable packers placed across the 8 1/2-in. open hole section. A multiphase production logging tool was selected to assess the production profile along its horizontal drain. With a target depth beyond the reach of conventional wireline, CT equipped with optical fiber emerged as the optimum solution to facilitate reach and overcome the weight and pumping limitations of wired CT. A comprehensive CT reach modeling exercise compared the performance of several 2-in. and 2 3/8-in. CT string designs and identified operational requirements and reach gains from CT hydraulic tractors. As a result, an engineered 2-in. CT tapered string of near 36,700 ft. was developed, capable of being equipped with optical fiber line, while delivering the required flow rate and differential pressure to the CT hydraulic tractor without compromising any operational safety margin. At the time of manufacturing, this was considered the longest CT string ever produced and fitted for downhole telemetry. The operation itself set new records for well interventions in mega-reach wells, with a CT reach above 35,500 ft. MD, including a hydraulic tractoring footage over 15,650 ft. MD with spaced slugs of chemical friction reducer.
This case study explains how to develop a safe, robust, and effective solution to mega-reach well challenges using the CT-conveyed optical fiber telemetry technology in one of the deepest wells in the field A, setting a new global record in CT reach. The lessons learned are now the reference for other operators in the Middle East and across the globe for performing interventions in wells that continue to be stretched in its extended reach. It also depicts why telemetry through optical fiber is key to the success of such projects and provides an overview of technology needs for the future of mega-reach well developments.
Linear and Nonlinear Controls of Wireline Logs on Automated Grain Size Estimation Using Machine Learning Approach
Authors: Anifowose Fatai Adesina , Alshahrani Saeed Saad , Mezghani Mokhles Mustafa 
Published: October 2021

Abstract
Wireline logs have been utilized to indirectly estimate various reservoir properties, such as porosity, permeability, saturation, cementation factor, and lithology. Attempts have been made to correlate Gamma-ray, density, neutron, spontaneous potential, and resistivity logs with lithology. The current approach to estimate grain size, the traditional core description, is time-consuming, labor-intensive, qualitative, and subjective. An alternative approach is essential given the utility of grain size in petrophysical characterization and identification of depositional environments.
This paper proposes to fill the gap by studying the linear and nonlinear influences of wireline logs on reservoir rock grain size. We used the observed influences to develop and optimize respective linear and machine learning models to estimate reservoir rock grain size for a new well or targeted reservoir sections. The linear models comprised logistic regression and linear discriminant analysis while the machine learning method is random forest (RF). We will present the preliminary results comparing the linear and machine learning methods. We used anonymized wireline and archival core description datasets from nine wells in a clastic reservoir. Seven wells were used to train the models and the remaining two to test their classification performance. The grain size-types range from clay to granules. While sedimentologists have used gamma-ray logs to guide grain size qualification, the RF model recommended sonic, neutron, and density logs as having the most significant grain size in the nonlinear domain.
The comparative results of the models' performance comparison showed that considering the subjectivity and bias associated with the visual core description approach, the RF model gave up to an 89% correct classification rate. This suggested looking beyond the linear influences of the wireline logs on reservoir rock grain size. The apparent relative stability of the RF model compared to the linear ones also confirms the feasibility of the machine learning approach.
This is an acceptable and promising result. Future research will focus on conducting more rigorous quality checks on the grain size data, possibly introduce more heterogeneity, and explore more advanced algorithms. This will help to address the uncertainty in the grain size data more effectively and improve the models performance. The outcome of this study will reduce the limitations in the traditional core description and may eventually reduce the need for extensive core description processes.
Quantification of Fluid Production Distribution in Deviated Wells with High Gas-Liquid Ratio Using a Flow Array Sensing Tool
Authors: González José Wilfredo , Linares Alejandro Jose , Rodriguez Diego Armando , Rivera Gerson Orlando , Schoepf Virginie M. , Abbassi Linda 
Published: October 2021

Abstract
The objective of this paper is to depict the quantification of the production rates of the different phases in deviated wells with high gas-liquid relation using the Flow Array Sensing Tool (FAST). The readings of standard Production Logging Tools (fullbore flowmeter, density, and capacitance) are centralized, therefore they are affected if there is re-circulation of the heavy phase (liquid). The phase segregation and possible apparent down flow of the heavy phase makes it very difficult to determine the distribution of the produced fluids, and in some cases the spinner flowmeter tends to stop or gives inaccurate readings. The cause of these inaccurate readings is that the centralized spinner is affected by positive flow in the high side and negative flow in the low side of the wellbore, and the spinner shows no flow or even apparent downhole flow, when there is a real positive flow.
The FAST tool used during the acquisition of the production logs is an ultracompact production logging tool (3 ft long) that is capable to measure multiphase flows with an array of 8 sensors, two in each arm and located 90° apart. These sensors are based on MEMS (Microelectromechanichal Systems), and among the interchangeable sensors we have optical probes that takes ultra-rapid measurements of the refractive index and can determine hold-up of water, oil and gas; the electrical probes that measures conductivity to differentiate hydrocarbons from water, and magnetic probes with micro-spinners to determine the flow rate. Both the three phase optical probes and the electrical probes have excellent response including water hold-ups over 90% that cannot be measured with a standard capacitance tool.
The data logged with FAST in deviated wells was processed and interpreted to obtain the apparent flow velocity profiles of each of the 4 micro-spinners and with the three phase optical probes, and the relative bearing curves the velocity maps, and hold-up maps where obtained. The velocity map showed that there was negative flow in the low side of the well and positive flow in the high side while the hold-up map showed the light phase (gas) in the high side of the well. Both maps showed clearly the flow pattern and were used to quantify the production of each perforation and the total rate matched closely the surface rate (within 2% deviation).
With the hold-up and velocity maps, the real flow rates were obtained with high confidence, and the flow pattern were shown clearly in deviated wells. The three phase optical probes, and electrical probes are excellent indicators of water and hydrocarbons inflow in a wide range of hold-ups.
Deployment of Downhole Mechanics Measurement System and Drilling Dynamics Modelling to Enhance Overall Drilling Performance Under Complete Mud Losses Environment
Authors: Echevarria Garnica Edgar , Moreira Gustavo Alves , Ruzhnikov Alexey 
Published: October 2021

Abstract
Drilling surface 16-in. and 12.25-in. sections in Middle East often accomplished by complete mud losses where downhole dynamic changed completely. To increase the performance and reduce drilling time the Positive Displace Motors (PDM) are used, however drilling under complete mud losses scenario may lead to a failure of the PDM, Measure While Drilling (MWD) tool, jar and any other components of the Bottom Hole Assembly (BHA). This manuscript describes the study of BHA dynamic in total loss scenario aiming to increase Rate of penetration (ROP) and decrease mechanical failures.
The changing in drilling dynamics under complete mud losses increases the severity of shock and vibrations (S&V), BHA whirl and, consequently, leads to downhole failures. Local practices have been used to control this risk by taking an over conservative approach, limiting Weight on Bit (WOB) and Revolution per Minute (RPM) to very low levels, affecting overall performance. To comprehensively understand the level of shock and vibrations under complete mud losses based on the modeled data, a Downhole Mechanics Measurement (DMM) system was used in the BHA to acquire the required data in real time to confirm and further improve the modeling of drilling dynamics. A drilling schedule with several combinations of WOB and RPM was developed to cover the full drilling envelop.
This study provided valuable understanding on the drilling dynamics while drilling under complete mud losses and allowed to clearly define the limiting boundaries to optimize ROP without jeopardizing the mechanical integrity of the BHA, particularly the PDM and drilling jar. On each formation drilled, RPM, WOB were changed to cover all possible combinations and, using the continuous real time measurement, ROP was optimized based on the level of shocks and vibrations experienced. Furthermore, the recorded mode Low and High-frequency data enabled to model the drilling dynamics and to quantify the effects of shocks and vibrations on the BHA. As a result, the wells have been drilled with significant ROP improvement (saving one day per run) and without downhole failures, achieving higher than expected performance results.
Development of Oil Formation Volume Factor Model using Adaptive Neuro-Fuzzy Inference Systems ANFIS
Authors: Alakbari Fahd Saeed , Mohyaldinn Mysara Eissa , Ayoub Mohammed Abdalla , Muhsan Ali Samer , Hussein Ibnelwaleed Ali 
Published: October 2021

Abstract
The oil formation volume factor is one of the main reservoir fluid properties that plays a crucial role in designing successful field development planning and oil and gas production optimization. The oil formation volume factor can be acquired from pressure-volume-temperature (PVT) laboratory experiments; nonetheless, these experiments' results are time-consuming and costly. Therefore, many studies used alternative methods, namely empirical correlations (using regression techniques) and machine learning to determine the formation volume factor. Unfortunately, the previous correlations and machine learning methods have some limitations, such as the lack of accuracy. Furthermore, most earlier models have not studied the relationships between the inputs and outputs to show the proper physical behaviors. Consequently, this study comes to develop a model to predict the oil formation volume factor at the bubble point (Bo) using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS model was built based on 924 data sets collected from published sources. The ANFIS model and previous 28 models were validated and compared using the trend analysis and statistical error analysis, namely average absolute percent relative error (AAPRE) and correlation coefficient (R). The trend analysis study has shown that the ANFIS model and some previous models follow the correct trend analysis. The ANFIS model is the first rank model and has the lowest AAPRE of 0.71 and the highest (R) of 0.9973. The ANFIS model also has the lowest average percent relative error (APRE), root mean square error (RMSE), and standard deviation (SD) of -0.09, 1.01, 0.0075, respectively.
Comparison of Porosity Change Due to Geochemical Reaction between Samples from High CO2 Field and Depleted Field
Authors: Sazali Wan Muhammad Luqman , Md Shah Sahriza Salwani , Misnan M Shahir , Kashim M Zuhaili , Othman Ahmad Faris , Kantaatmadja Budi Priyatna 
Published: October 2021

Abstract
When developing a high CO2 field, oil and gas companies must consider the best and most economical carbon capture and storage (CCS) plan. After considering the distance of the storage site and storage capacity, PETRONAS has identified 2 carbonate fields, known as X Field and N Field in East Malaysia as the potential CO2 storage site. Interestingly, both fields are different, as X field is a high CO2 green field, while N field is a depleted gas field. The research team’s initial hypothesis is that N Field would have more severe geochemical reaction between CO2, brine and carbonates compared to X Field, since X field is already saturated with CO2. In order to test the hypothesis, samples from these two fields were selected to undergo static batch reaction analysis, and changes in porosity were determined using Digital Core Analysis (DCA). Both X and N fields are carbonate gas fields, with aquifer zone located below gas zones. The aquifer zones are the preferable CO2 injection zone because the deeper the zone, the longer it will take for the plume migration to happen. For static batch reaction analysis, samples each field were selected from the aquifer zone. After Routine Core Analysis (RCA) and Quality Control (QC), the samples were scanned under the high resolution microCT scan, before they were saturated into the respective synthetic brine. After saturation is completed, both brine and samples were placed inside a batch reactor, where the reactor’s pressure and temperature are set according to the field’s pressure and temperature. Once stabilized, the supercritical CO2 is injected into the brine, and was left for 45 days with constant observation. After aging with supercritical CO2, the samples were then scanned under microCT scan once again, using the same resolution, before being analysed via image processing software. Using registration algorithm software, both pre and post CO2 aging images were overlapped and subtracted digitally. The difference images were analyzed to determine the change in porosity. Samples from X Field has around 1% p.u. increase in porosity, while samples from N field shows increment of 2% p.u. porosity. While N field (depleted field) has higher reaction compared to X field (high CO2) field as per hypothesis, the difference is very minimal, which is much less than expected. The usage of DCA in the analysis enabled the team to determine minute changes that were happening during CO2 batch reaction. Without DCA, the 1% changes usually regarded as equipment’s error margin. The next step would be modelling, where the lab results will be upscaling into field scale, for modelled longer period of time. Hence, although the porosity changes between X and N field are very small under laboratory condition, it can have greater impact in field scale.
Experimental Investigation of a Novel Nanosilica for Blocking Unwanted Water Production
Authors: Alabdrabalnabi Mohammed , Almohsin Ayman , Huang Jin , Sherief Mohammed 
Published: October 2021

Abstract
Nanotechnology is the design and application of engineered nanoparticles with one minimum dimension in the range of 1 to 100 nanometers. To achieve a specific target, innovative methods are highly required to overcome the challenges in the oil and gas industry, such as undesired water production. Herein, we present an advanced nanosilica, a new eco-friendly, cost-effective, and promising approach to control undesirable water production.
The objective of this work is to evaluate our nanofluid system that can be used for water management in different water production mechanisms, including: high permeability streak, wormhole, and fractured reservoirs. A systematic evaluation of novel nanosilica/activator for water shut-off application requires an examination of the chemical properties before, during, and after gelation at given reservoir conditions. The placement of this water shut-off system is highly dependent on gelation time and viscosity. Therefore, we emphasized in this study on investigating these gelation kinetics by conducting extensive rheology experiments at varied temperatures and activator concentrations. We have looked into evaluating the optimum breaker for the gel as a contingency plan for improper placement.
Measurements of the nanosilica fluid’s initial viscosity exhibited a low viscosity, less than 10 cP at normal temperature and pressure (NTP) conditions; this provides significant benefit for mixing at surface and pumping requirements for pilot testing. The nanosilica gelation time can be tailored by adjusting activator concentration to match field job design at a given temperature, which is more than 200°F. The gelation time revealed an exponential relationship with temperature and reversible proportionality. The nanosilica gel proved to be a thermally stable fluid system along with different activation ratios. For breaker tests, the gellant fluid showed complete breakdown at altered temperatures to mimic downhole conditions. Our lab observations conclude that nanosilica fluid is verified to be acceptable as a water shut-off system for field applications.
This novel nanofluid system is a promising technology to control water production from oil wells. The system has low initial viscosity that can be injected in porous media without hindering the injectivity and getting at risk of fracking the sand. In case of inappropriate placement, the fluid can break down entirely using a non-damaging chemical breaker instead of using mechanical approaches that might damage the completion.
Effect of GnRH Agonist Alone or Combined With Different Low-dose hCG on Cumulative Live Birth Rate for High Responders in GnRH Antagonist Cycles: a Retrospective Study
Authors: He Yuxia , Tang Yan , Chen Shiping , Liu Jianqiao , Liu Haiying 
Published: October 2021

Abstract
Background: There is insufficient evidence regarding the impact of dual trigger on oocyte maturity and reproductive outcomes in high responders. Thus, we aimed to explore the effect of gonadotropin-releasing hormone agonist (GnRHa) trigger alone or in combination with different low-dose human chorionic gonadotropin (hCG) regimens on rates of oocyte maturation and cumulative live birth in high responders who underwent a freeze-all strategy in GnRH antagonist cycles.Methods: A total of 1343 cycles were divided into three groups according to different trigger protocols: group A received GnRHa 0.2 mg (n=577), group B received GnRHa 0.2 mg and hCG 1000 IU (n=403), and group C received GnRHa 0.2 mg and hCG 2000 IU (n=363). Results: There were no significant differences in age, body mass index, and rates of oocyte maturation, fertilization, available embryo, and top-quality embryo between the groups. However, the incidence of moderate to severe ovarian hyperstimulation syndrome (OHSS) was significantly different between the three groups (0% in group A, 1.49% in group B, and 1.38% in group C). For the first frozen embryo transfer (FET) cycle, there were no significant differences in the number of transferred embryos and rates of implantation, clinical pregnancy, live birth, and early miscarriage between the three groups. Additionally, the cumulative ongoing pregnancy rate and cumulative live birth rate were not significantly different between the three groups. Similarly, there were no significant differences in gestational age, birth weight, birth height, and the proportion of low birth weight among subgroups stratified by singleton or twin.Conclusions: GnRHa trigger combined with low-dose hCG (1000 IU or 2000 IU) did not improve oocyte maturity and embryo quality and was still associated with an increased risk of moderate to severe OHSS. Therefore, for high responders treated with the freeze-all strategy, the GnRHa single trigger is recommended for final oocyte maturation, which can prevent the occurrence of moderate to severe OHSS and obtain satisfactory pregnancy and neonatal outcomes in subsequent FET cycles.
Progesterone Gel and Placebo were Equally Effective in Preventing Preterm Birth Among Women with Preterm Labor
Authors: Stjernholm Ylva Vladic , Vladic Tomislav , Marchini Giovanna 
Published: October 2021

Abstract
Introduction The aim of this trial was to evaluate the effect of maintenance treatment with vaginal progesterone gel compared to placebo in preventing preterm birth after the onset of preterm labor.Methods A randomised controlled trial in Sweden in 2009 − 18. Women with preterm labor were randomized to daily doses of progesterone gel 90 mg (n = 29) or placebo (n = 29) after standard treatment with intravenous tocolytics. Women with intravenous tocolytics alone served as controls.Results The latency to delivery was 58 ± 34 days with progesterone and 64 ± 51 days with placebo (p = 0.83), compared to 2 ± 2 days in the control group (progesterone and placebo vs control p < 0.001). The rate of preterm birth before 34 weeks was 34 % after progesterone and 38 % after placebo (p = 0.34) compared to 100 % in the control group (p < 0.001 respectively). The composite neonatal morbidity (p = 0.65) and neonatal intensive care unit admission (p = 0.12) were comparable between the progesterone and placebo groups, but lower in these groups compared neonates of women in the control group (p < 0.001 respectively). Conclusion Maintenance treatment with progesterone gel and placebo were equally effective in preventing preterm birth among women with preterm labor. Both progesterone and placebo prolonged pregnancy more effectively than intravenous tocolysis alone. We hypothesize, that the acidic gel base reinforced the biochemical barrier at the uterine cervix, which counteracted ascending pathogen invasion and subsequent inflammation and thereby delayed preterm birth. The present results suggest, that non-hormonal agents that reinforce the biochemical cervical barrier can be useful for the prevention of preterm birth in clinical practice.