bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance Review of Chemical Sand Consolidation and Agglomeration for Maximum Potential as Downhole Sand Control: An Operator’s Experience
Authors: Hassan Nur Atiqah , Yeap Wei Jian , Singh Ratan , Nik Khansani Nik Zarina 
Published: November 2020

Abstract
Uncontrolled sand production has caused serious complication and monetary loss in oil and gas assets worldwide especially in mature fields. It is known to be drastically limiting the production rates and damaging downhole and surface equipment, inducing the risk of catastrophic failure. Sand production is commonly associated with contributing factors such as unconsolidated formation, initiation of water breakthrough and changes in rock stresses due to depleted reservoir pressure. To mitigate sand production, operators often opt for applying mechanical or chemical downhole sand control methods. This paper will discuss about the performance results and lessons learnt from the application of chemical treatment for downhole sand control over several mature fields in Malaysia.
Chemical sand consolidation (SCON) and sand agglomeration have been identified as effective chemical treatment to control sand production downhole. Both treatments involve injection of chemical into immediate near wellbore area of the reservoir with the aim to improve the strength of the incompetent formation and thus reducing the tendency for sand production. In most cases, SCON treatment consists of injecting fluid containing adhesive or resin for binding the sand grains while the main mechanism of sand agglomeration involves increasing the attraction between sand particles through processes such as polymer bridging interactions and charge neutralization. Stringent candidate screening and detailed pre-job planning are crucial in ensuring the success of both SCON and sand agglomeration treatment.
Over the past few decades, there were about 20 SCON treatment jobs and 3 sand agglomeration jobs were performed across several Malaysia fields with varying service providers and chemicals. The overall success rates for sand consolidation and sand agglomeration are 75% and 66% respectively. To evaluate the effectiveness of the chemical treatment for downhole sand control, analysis was conducted to study the effects of parameters such as completion type, perforation length, formation permeability, clay content, well preparation, formation temperature and placement methods.
This paper presents lesson leamt and best practice from several chemical SCON and sand agglomeration treatments performed over mature fields in Malaysia. Case studies for several wells will be examined to highlight the lesson learnt which are essential to further enhance the success of chemical SCON and agglomeration treatment. Best practice shall be incorporated into future campaigns to ensure chemical treatment as a successful means to control sand production downhole in a low-cost environment.
Source-Less Method Case Study: Integrated LWD NMR and LWD Azimuthal Resistivity Application in Low Resistivity and Low Contrast Reservoir in Bohai Bay
Authors: Zhu Meng , Cui Yunjiang , Xu Jinxiu , Chen Hongbing , Wang Ruihong , Wei Gang , Holger Thern , Zeng Xianlei , Liang Yi 
Published: November 2020

Abstract
The use of radioactive source porosity measurements is strictly prohibited in Bohai Bay, China. As an alternative, logging-while-drilling nuclear magnetic resonance (LWD-NMR) has been applied.
In one block of the Bohai Bay field, it is a big challenge to identify and quantify hydrocarbon reservoir sections due to little resistivity contrast between reservoirs and water zones. LWD-NMR technology and the azimuthal resistivity tool is able to solve this challenge. The low-gradient LWD-NMR tool not only measured porosity also provide T2 distributions, which can be used for fluid type characterization. The azimuthal resistivity tool has a deep azimuthal resistivity measurement that can identify nearby bed boundaries, up to 5 m from the borehole, while drilling. This information is available in real-time to the operator for decisions while drilling. The combination of the two measurements is capable of differentiating physical properties of the reservoir and providing information on fluid types. Thus, the operator can easily make decisions to optimize the wellbore placement and perform an accurate petrophysical evaluation of the reservoir.
A pilot hole and a horizontal hole are presented in this paper to show the advantages of LWD-NMR and the azimuthal resistivity respectively. In the pilot hole, the LWD-NMR has been used for fluid typing which can give a clear petrophysical interpretation of the reservoir fluids. Because in this low-resistivity contrast reservoir, it is difficult to differentiate oil zones (10+ Ohmm) and water zones (9- Ohmm) from resistivity data. The light oil, however, shows a much slower NMR T2 relaxation time than the water. Based on the identification of oil versus water by NMR in the pilot hole, three horizontal wells were successfully drilled in the oil zone. In one of them, LWD-NMR and azimuthal resistivity have been employed simultaneously for optimal wellbore placement by enabling to drill in the best part of the reservoir. The LWD-NMR measurements indicated reliably the presence of hydrocarbons and provided important reservoir properties. The azimuthal resistivity measurements identified the reservoir boundaries and the distance to them.
Under complex reservoir conditions as encountered in Bohai Bay, azimuthal resistivity and LWD NMR prove to be an accurate and robust source-less measurement combination. LWD NMR can effectively replace the traditional density-neutron source measurements for porosity. More importantly, the combination with azimuthal resistivity provides the operator with additional critical information for optimal wellbore placement and strengthening the confidence in petrophysical interpretation results.
A Novel Stimulation Design Approach Revives a Challenging Gas Field
Authors: Almulhim Abdulrahman , Hamid Saad , Khan Abdul Muqtadir , Hoong Chan Choon 
Published: November 2020

Abstract
Multiple attempts to commercially produce from a horizontal well in a challenging sandstone formation completed with the plug-and-perf method were rendered unsuccessful. An innovative stimulation strategy was proposed for the next candidate in an attempt to improve post-fracturing productivity. Three different types of proppant fracturing treatments were performed as a first-time application, including hybrid slickwater treatment, low-guar crosslinked treatment, and CO2 foam fracturing.
A hybrid design combining high-rate slickwater at the beginning and low-guar-loading crosslinked gel at the end of the treatment was pumped in two stages. This allowed minimizing the crosslinked fluid pumped while enhancing fracture half-length. Second, conventional low-guar fracturing was implemented in four stages. Crosslinked gel loading was reduced by 25% compared to gel that was utilized in offset wells. Finally, a CO2 foam fracturing design with a novel biopolymer linear fracturing fluid was implemented in the last stage. This reduced water consumption and improved the chance of increased gas production by yielding a higher-conductivity fracture network.
Friction pressure for CO2 foam was calibrated using bottomhole gauge data that was obtained with downhole gauges run prior to the calibration testing. The new calibrated friction numbers were then used for the bottomhole treating pressure calculation during the treatment. CO2 foam fracturing was found to be a significant success for this well based on multiple evaluation criteria. First, the use of foam helped conserve 1,000 bbl of freshwater compared to conventional stages. Second, the foam treatment allowed two times faster cleanup compared to other stages, based on cleanup time normalized over fluid volumes. Finally, production logging results showed that the foamed treatment achieved better production compared to other treatments in the well, considering productivity index (PI) normalized by the proppant mass, porosity, and zone mobility. The CO2 stage normalized PI was significantly higher than the other stages in the well. After the well was cleaned up, a production log was conducted, and it was analyzed to corroborate the higher production: 70% of the production contribution was seen from the CO2 treatment interval.
In most of the literature, estimates of the friction correlations for foams are based on empirical data. This paper gives the calculations of friction pressure based on field data. The combination of measured bottomhole data and post-cleanup production logging demonstrates the potential productivity improvements that can be achieved through novel design approaches. This type of data is rare in the industry and can help to improve the design of foamed fracturing treatments.
RSS and Motor Directional Analysis: Modelling the Effect of Local Doglegs on RIH of Completions and Casing
Authors: Nobbs Benjamin , Menand Stephane , Dao Ngoc-Ha 
Published: November 2020

Abstract
Rotary steerable systems (RSS) and steerable motors pose their own unique challenges when modelling the bottomhole assembly (BHA) directional behavior. This paper aims to present a methodology that allows the anticipation of problems such as mechanically stuck pipe or lock up situations when running in hole casing or completion strings.The methodology consists of 3 tasks: evaluation of intermediate doglegs and wellbore tortuosity using a unique Rock-Bit-BHA analysis, modelling of the casing deformation including potential centralization and then modelling the run in hole (RIH) of the completion. The directional capabilities of a BHA are affected significantly by the selection of the drilling bit, type of directional drilling driving system and the type of formation. The resulting trajectory can be either very smooth or very tortuous with significant additional local doglegs. The deformation of the casing as well as the completion post buckling analysis is completed using a robust and field validated 3D stiff string Torque & Drag & Buckling model. This methodology can be applied before, during or after the well has been drilling. Used before or during the well construction process, an indication can be given as to whether the casing or completion can reach total depth (TD) using planned or actual data. Used after a lockup or stuck pipe incident, the methodology can give an indication if tortuosity was a contributing factor. Various field cases are presented and clearly show the benefit of the methodology including post-analysis of stuck standalone-screen (SAS) completion string in complex 3D drain and pre-analysis of completion run in hole (RIH) targeting a specific drain. Correctly evaluating the risk of BHA, casing and/or completion strings getting stuck or locked-up when RIH can ultimately provide a template for ultimate reduction of non-productive time (NPT).
Monitoring and Modelling Condensate Banking Effects with the Ichthys Field Production Data
Authors: Iizuka Ryo 
Published: November 2020

Abstract
The Ichthys gas-condensate field is situated in the Browse Basin, North West Shelf of Australia, and the field production commenced in July 2018. The Brewster Member, one of the two reservoirs in the field, is a liquid-rich sandstone reservoir. One of the major uncertainties is the degree of well productivity impairment, caused by condensate banking since the dew point pressure is close to the initial reservoir pressure. The objectives of this study are to evaluate the condensate banking impact on well production performance, and to establish a modelling methodology to consider the condensate banking effect in a full-field simulation model, based on the field production data.
Permanent downhole gauges are deployed in the field, and thus, downhole pressure can be monitored continuously. We conducted high rate tests for selected wells to monitor well productivity impairment from the condensate banking. This production data was history-matched with a compositional sector model by applying Local Grid Refinement (LGR) and Velocity-Dependent Relative Permeability (VDRP) to account for more accurate physics in the near-well region. With the tuned VDRP model, skin trends were predicted to increase with various gas rates, and a skin correlation was established as a function of this gas rate. This correlation is applied to the full-field simulation where LGR and VDRP cannot be applied due to a simulation time constraint.
The skin correlation was validated through the history matching, using the full-field model and was used to predict the future field production performance. We need continuous monitoring of the condensate banking effect, to further validate the correlation, because the production data used in this study is less than one-year duration. The correlation is then flexible enough to tune the history matching when necessary.
We present the monitoring and modelling of the condensate banking effect with the actual production data. The implementation of the proposed well modelling will help reservoir engineers in considering the condensate banking effect in the field production forecast.
New Vision into Relative Permeability Estimation Using Artificial Neural Networks
Authors: Kalam Shams , Khan Mohammad , Mahmoud Mohamed , Khan Rizwan Ahmed , Abu-Khamsin Sidqi A. 
Published: November 2020

Abstract
Artificial intelligence (AI) has proven to be the smartest predicting tool in the oil and gas industry. In this paper, Artificial Neural Network (ANN) algorithm was applied to build two new empirical correlations to predict relative permeability profiles of oil-water two phase flow in the reservoir for both sandstone and carbonate reservoirs. The proposed model evaluates the relative permeability as a function of porosity, rock absolute permeability, initial water saturation, residual oil saturation, wettability index and water saturation. Accordingly, relative permeability to water and oil are respective outputs. Real data of both sandstone and carbonate reservoirs taken from literature were used in the development of the new empirical correlations. Multiple realizations with various hidden layer neurons were run to find the best scenario; and maximum coefficient of determination (R2) was designated as the finest case. The weights and biases values were found for the models of relative permeability to water and oil after proper training and are presented in this paper. Tan-sigmoid and linear transfer functions were utilized in the hidden and output layers, respectively. Neural Network was trained using Levenberg-Marquardt back-propagation algorithm. The novel ANN model was able to accurately estimate relative permeability to oil and water for an unseen data set of 319 real data points. Root mean squared error for both models are near to zero, while R2 for relative permeability to oil and water is 0.92 and 0.98, respectively. The relative permeability models are presented in the form of an actual mathematical correlation. The use of the developed ANN models significantly saves time and cost for conducting experiments for relative permeability measurements.
Development of a Model and Simulation Tool to Predict Hydrate Growth in Flowlines for Gas Hydrate Production
Authors: Sakurai Shunsuke , Norris Bruce , Hoskin Ben , Choi Joel , Nonoue Tomoya , Eric May , Aman Zachary 
Published: November 2020

Abstract
Natural gas hydrate has attracted interest as an energy resource capable of meeting the expected growth in global energy demand. Several key issues remain to be tackled to enable commercial production, one of which is gas hydrate re-association in production lines, where significant volumes of water are co-produced with free gas. To predict this behavior, we introduce a model and simulation tool tailored towards hydrate growth in water-dominant turbulent flow.
We have produced a model to predict the growth rate of hydrate in water dominant systems, integrated into an in-house pseudo-steady-state multiphase flow simulator, named HyFAST. This is a mass transfer limited model where the growth rate is limited by the dissolution of guest gas molecules into the water-continuous phase. It considers the effect of interfacial gas-water bubble surface area, the degree of turbulence on mixing, and changes in bulk viscosity caused by hydrate particle formation. The tool is deployed to estimate the hydrate volume formed in production lines during the second offshore methane hydrate production test in Japan.
Initially, the model was validated in an experimental study against flowloop data, where, at worst, model predictions showed order of magnitude agreement with experimental growth rates; following this the model was integrated into an overall flow simulation tool used for larger scale predictions. The offshore production test was designed to use two separate lines to produce gas and water, however, some gas was entrained into the water production line, posing a risk of re-association. As such, our primary focus was on this water production line, approximately 1 km in length, rather than the gas production line, which generally remained outside the hydrate stability region. Our simulation predictions showed that the hydrate volume in the water production line was less than 5 vol%. Coupled with flowloop data which showed that blockages did not occur in similar systems up to 20 vol% hydrate, this suggests there was not a significant hydrate blockage likelihood in the offshore production test. These initial results suggest that the model may scale well from lab to field, and that such simulation tools can prove useful in discussing the consequences of hydrate re-association.
A new model and simulation tool were developed to predict the rate and extent of hydrate growth in water-dominant flow. These were used to predict hydrate formation in both flowloop experiments and actual production lines. The validation results showed that the approach may prove useful in evaluating hydrate blockage propensity in future gas hydrate production.
Integrated Field Management System for LNG Assets: Optimising Recovery and Managing Deliverability under Complex Constraints
Authors: Khan Osama Hasan , Ali Samad , Elfeel Mohamed Ahmed , Biniwale Shripad , Dandekar Rashmin 
Published: November 2020

Abstract
The sustained increase in global demand for cleaner fuels continues to drive the gas industry growth. Liquefied natural gas (LNG) has been a key enabler for this growth by making sizeable remote gas re-serves, which are unreachable by pipeline, accessible to the major and emerging gas markets. Every segment of the LNG supply chain has its own set of technical challenges. On the upstream side, many gas resources require significant pre-treatment before liquefaction, and the feed gas to the LNG facility is typically a mixture of various compositions from multiple sources; this composition mix evolves over the life of the project. The main challenge is development planning for the contributing reservoirs under the constraints imposed by the processing facility– managing reservoir deliverability, scheduling & sequencing of wells, and downtime management while maintaining the inlet stream specification. To aid with long-term planning for such assets, a virtual field management system is needed that can emulate a real-world hydrocarbon producing asset by capturing all operational constraints, resource lim-its, and complex operating logic.
This paper describes a comprehensive field management framework that can create an integrated vir-tual asset by coupling reservoir, wells, network, and facilities models and provides an advisory system for efficient asset management. The field management component can replicate any operational logic, exercises holistic control over the sub-surface model, integrates with the surface network model, and provides optimization capabilities. This paper demonstrates this for a complex LNG asset that is fed by sour gas of different compositions from multiple reservoirs.
We describe the different levels of constraints the asset needs to operate under, including treatment plant capacity, the LNG production capacity, the contractual LNG specifications, the disposal of gas impurities and imposes them on the model by utilizing a flexible and extensible logic framework. Con-straints applied at different levels can be mutually competing and their combination with recovery opti-mization goals increases complexity. The unified field management system uses a robust scheme to bal-ance the coupled system under these constraints while optimizing overall recovery. The optimization is enabled through the ability provided by the field management system to query and retroactively control flow entities during the simulation at the desired frequency.
Customization through scripting was necessary to implement this advanced logic and was enabled by the extensible nature of the field management framework. This extensibility, along with native capabili-ties, ensures that any level of complexity can be captured, and the workflow described in this paper can be applied to any hydrocarbon producing asset for short-term and long-term development planning.
Health-risk Investigation Among First-grade School Children From Shanghai Chemical Industry Park (SCIP): A Cross-sectional Study
Authors: Xiao Shuang , Xu Mingjia , Wang Lihua , Tu Wei , Yu Lili , Sun Yongqi , Zhang Jun , Wang Wenge , Hu Jian , Hu Yi , Zhou Xuesong , Cai Qingtao , Zhang Yaning , Zhang Zhijie 
Published: November 2020

Abstract
BackgroundShanghai Chemical Industry Park (SCIP), located in Jinshan District, is the largest industrial zone in China. However, the impact on the residents’ health has not been assessed. The study aimed to identify the impact of living in chemical industrial areas on the health of first-grade studentsMethodA cross-sectional study was conducted among first-graders between May and June 2016 in Jinshan District using experimental examinations and questionnaires. Demographic statistics and hematological parameters were summarized. Geographical distribution and high-risk clusters of prevalence of diseases and birth status were depicted. Multivariate logistic model was used to analyze the differences in the prevalence of diseases and symptoms between chemical and nonchemical industrial areas after adjusting for potential factors.ResultA total of 4821 first graders were included in the study. Mean age was 7.2 (±0.41) years. The prevalence of respiratory, digestive, and skin diseases was 0.229, 0.042, and 0.168, respectively. We observed one spatial cluster each for respiratory diseases (RD) and skin diseases, respectively. Significant differences in birth defects were not observed. Some significantly different hematological parameters and higher prevalence of RD in nonchemical industrial areas might indicate pollutant exposures in nonchemical industrial areas. The study revealed a possible positive association between environmental factors and RD.ConclusionStrong evidence regarding the main impact of SCIP on the health of school children was not observed. Governments and parents might need to pay more attention to indoor and other environmental management. Long-term health effects of chemical industries should be continuously monitored.