bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zipper Fracturing of Horizontal Cluster Wells: Game Changing Unconventional Fracturing in UAE
Authors: Wu Yang , Sorensen Ole , Lazreq Nabila , Luo Yin , Bukovac Tomislav , Arali Vaishak 
Published: December 2021

Abstract
Following the increase in demand for natural gas production in the United Arab Emirates (UAE), unconventional hydraulic fracturing in the country has grown exponentially and with it the demand for new technology and efficiency to fast-track the process from fracturing to production. Diyab field has historically been a challenging field for fracturing given the high-pressure/high-temperature (HP/HT) conditions, presence of H2S, and the strike-slip to thrust faulting conditions. Meanwhile, operational efficiency is necessary for economic development of this shale gas reservoir. Hence "zipper fracturing" was introduced in UAE with modern technologies to enable both operational efficiency and reservoir stimulation performance.
The introduction of zipper fracturing in UAE is considered a game changer as it shifted the focus from single-well fracturing to multiple well pads that allow for fracturing to take place in one well while the adjacent well is undergoing a pumpdown plug-and-perf operation using wireline. The overall setup of the zipper surface manifold allowed for faster transitions between the two wells; hence, it also rendered using large storage tanks a viable option since the turnover between stages would be short. Thus, two large modular tanks were installed and utilised to allow 160,000 bbl of water storage on site. Similarly, the use of high-viscosity friction reducer (HVFR) has directly replaced the common friction reducer additive or guar-based gel for shale gas operation. HVFR provides higher viscosity to carry larger proppant concentrations without the reservoir damage, and the flexibility and simplicity of optimizing fluid viscosity on-the-fly to ensure adequate fracture width and balance near-wellbore fracture complexity. Fully utilizing dissolvable fracture plugs was also applied to mitigate the risk of casing deformation and the subsequent difficulty of milling plugs after the fracturing treatment. Furthermore, fracture and completion design based on geologic modelling helped reduce risk of interaction between the hydraulic fractures and geologic abnormalities.
With the application of advanced logistical planning, personnel proficiency, the zipper operation field process, clustered fracture placement, and the pump-down plug-and-perforation operation, the speed of fracturing reached a maximum of 4.5 stages per day, completing 67 stages in total between two wells placing nearly 27 million lbm of proppant across Hanifa formation. The maximum proppant per stage achieved was 606,000 lbm.
The novelty of this project lies in the first-time application of zipper fracturing, as well as the first application of dry HVFR fracturing fluid and dissolvable fracturing plugs in UAE. These introductions helped in improving the overall efficiency of hydraulic fracturing in one of UAE's most challenging unconventional basins in the country, which is quickly demanding quicker well turnovers from fracturing to production.
Interpretation Challenges and Solutions for Real-Time Asphaltene Paramagnetic Sensing at the Wellhead
Authors: Lovell John , Abdallah Dalia Salim , Fonseca Rahul Mark , Grutters Mark , Punnapala Sameer , Kulbrandstad Omar , Meza Daniel , Baez Jorge 
Published: December 2021

Abstract
Asphaltene deposition presents a significant flow assurance to oil production in many parts of the Middle East and beyond. Until recently, there had been no intervention-free approach to monitor deposition in the asphaltene affected wells. This prompted ADNOC to sponsor MicroSilicon to develop of an intervention less real-time sensor device to monitor asphaltene deposition. This new state-of-the-art device is currently installed and automatically collecting data at the wellhead and nearby facilities of an ADNOC operated field.
Historic ways of measuring asphaltene in oil relied upon laboratory processes that extracted the asphaltene using a combination of solvents and gravimetric techniques. Paramagnetic techniques offer a potentially simpler alternative because it is known that the spins per gram of an oil is a constant property of that oil, at least when the oil is at constant temperature and pressure. Taking the device to the field means that any interpretation needs to be made independent of these properties. Additionally, the fluid entering the sensor is multiphase and subject to varying temperature and pressure which raises challenges for the conversion of raw spectroscopic data into asphaltene quantity and particle size. These challenges were addressed with a combination of hardware, software and cloud-based machine learning technologies.
Oil from over two dozen wells has been sampled in real-time and confirmed that the asphaltene percentage does not just vary from well to well but is also a dynamic aspect of production, with some wells having relatively constant levels and others showing consistent variation. One other well was placed on continuous observation and showed a decrease in asphaltene level following a choke change at the surface. Diagnostic data enhanced by machine learning complements the asphaltene measurement and provides a much more complete picture of the flow assurance challenge than had been previously been available.
Automated Intelligent Alarms to Monitoring and Identify Liquid Loading Challenge for Giant Depletion Gas Condensate Fields
Authors: Alsaeedi Ayesha Ahmed Abdulla Salem , Elabrashy Manar Maher Mohamed , Alzeyoudi Mohamed Ali , Albadi Mohamed Mubarak , Soni Sandeep , Raj Apurv , Alkuwaiti Hamda , Sabat Siddharth 
Published: December 2021

Abstract
Depleted well monitoring is a crucial task to ensure continuous production without facing substantial issues that withhold the production, such as liquid loading. Utilizing an integrated digital production system and custom intelligence alarms functionality can help identify and analyze this bottleneck using physics-based model estimations that can help users take preventive actions, leading to saving cost, time, and effort. This paper demonstrates the identification of the liquid loading using custom intelligence alarms and an automated framework.
Initially, a representative compositional well model is added to the digital twin solution enabling the automated well analysis workflow. Subsequently, custom intelligence alarms guidelines are configured to keep the well's performance and production rates under supervision with a notification capability when parameters violate the guidelines.
Along with various well performance parameters being analyzed, two critical parameters for liquid loading debottlenecking, critical unloading velocity and the In-situ velocity, are investigated in the system for each well as the function of depth along well's completion. Moreover, advanced dashboards report the analysis output in an informative manner, guide users’ engineering judgment to take preventive decisions.
As a result of the custom intelligence alarm, gas condensate wells suffering from liquid loading were predicted and identified. Based on the production parameter and target monitoring, these wells were unable to produce their expected mandate resulting in violating the set of production parameters guidelines. Identified wells were run through production gas rate sensitivity analysis using the analytical tool, and in conclusion, the optimal production rate was calculated. Producing the well below this critical rate causes the In-situ velocity to drop below critical unloading velocity. Additionally, using the tuned and calibrated network model, the operating choke was identified to maintain the stable flow in the well and avoid further liquid loading. This choke size was provided to field operation for implementation and saved the cost and man-hour spent during the flowing gradient surveys. The case study demonstrates significant production improvements observed for these wells, thereby significantly reducing cost and time.
Using the integration of the latest production optimization platforms and custom intelligence alarm provides tools to identify wells that are currently experiencing liquid loading challenges and healthy wells that might come under the liquid loading category in the course of production, thus helping in taking proactive remedial action. Furthermore, the integrated framework provides erosional velocity-related data, which acts as a guideline while optimizing gas production.
Virtual Drilling Environments Enable Long Distance Training in Unprecedented Times of Sanitary Emergency
Authors: Ferrara Paolo , Dal Forno Luca , Ricci Maccarini Giorgio , Demetri Katia , Neboli Monica , Tonarelli Francesca 
Published: December 2021

Abstract
During the last five years, a digital training solution, based on Virtual Reality, for immersive and collaborative experience on a virtual drilling rig, was developed and updated by company’s Well Operations Department in collaboration with Corporate University Infrastructures. This paper will present the digital training environment and its applications, including a discussion of all supporting deployment facilities.
The digital Drilling Environment consists in the full digitalization of a last generation offshore semi-submersible drilling rig. On the Virtual Rig, it is possible to access all equipment and workplaces, re-play past operations from a company’s database and interact with a number of safety situations from inductions and drills to the reproduction of a series of real incidental events. The virtual environment is accessible in dedicated 3D rooms, by using Virtual Reality headsets, stand-alone PCs, via lan or by remote internet connections.
The new training method, which proved incremental to traditional approaches, turned out to be decisive in supporting long distance education in unprecedented times of sanitary emergency. In particular, the virtual drilling rig ensures an immersive and collaborative experience of rig operational and emergency conditions, while granting a safe and protected environment where knowledge can be quickly achieved. The necessity to focus on new long distance training approaches and the further enhancement of the virtual drilling environment portability were boosted by the particular world situation, which led to the necessity to address, manage and review the overall company’s educational strategies. This paper is made available to discuss suggestions and to present all lessons learnt.
Vertical Integration Strategy Implementation Through Hybrid Upstream and Downstream Concession Agreements
Authors: Al Jarwan Dr. Abdulla , Sheikh Fathesha 
Published: December 2021

Abstract
Upstream developments in prolific oil and gas fields are highly profitable and hence attract various investors/partners, whereas Downstream developments profitability is margin based and challenging under certain situations to receive similar interest for investment in the same location. Vertical Integration Strategy implementation through hybrid upstream and downstream concession agreements can help address this issue.
The seventies witnessed major changes in the oil industry's structures and strategies resulting from the nationalization of oil and gas reserves. This ultimately led to a separation between the upstream sector with national oil companies (NOCs) controlling most of the world reserves and crude production, and the downstream sector with the international oil companies (IOCs) controlling the largest share of the refining and marketing aspects in the main consuming countries. In the recent past, NOCs have started forward integration of its upstream sector with downstream sector to take advantage of the synergies and increase profitability. This paper takes the strategy a step more forward by exploring the possibility of developing oil and gas assets through a hybrid upstream/downstream concession agreement that can be awarded by the host government.
The model hybrid agreement is built by integrating a typical upstream concession agreement with downstream equity-based joint venture (JV) agreement. It also takes the learnings from Production Development Production Sharing Agreement (DPSA) applied in the development of a Gas-To-Liquids (GTL) asset or Liquefied Natural Gas (LNG) asset which are usually developed as an integrated upstream and downstream business model. It is also feasible to build the hybrid agreement based on upstream Production Sharing Agreement (PSA) instead of a Concession Agreement.
The paper will discuss how the hybrid upstream and downstream concession agreement is built and how it will distribute the risk and rewards across the entire value chain for investors, expand the scope of investment and support in the economic development of the host country.
Research and Application of Micro-Expansion and Anti-Channeling Cement Slurry System in Agadem Oilfield
Authors: Wang Gang , Duan Dexiang , Li Wanjun , Qian Feng , Qin Zhengli , Zhong Zhao , Zhou Chuan , Bahedaer Baletabieke , Jing Ning , Ye Dongqing , Gao Qingyun , Xiao Yue , Li Ganlu , Liu Jitong , Zhang Guobin , Li Shaohua 
Published: December 2021

Abstract
The overall liner cementing qualification rate is only 40% in Agadem block of Niger, The cement slurry system used in the field has a UCA transition time of 43min, and an expansion rate of -0.03% in 24h, which result in a poor anti-gas channeling performance. The expansive agent and the anti-gas channeling toughening agent of anti-channeling agent were optimized through experiment study. A novel micro-expansion anti-gas channel cement slurry system which is suitable for Agadem block was obtained through experiment optimization study: 100% G +2 ∼ 4% fluid loss agent +3 ∼ 4.5% anti-channeling agent +1 ∼ 2% expansion agent-100S +0.15 ∼ 0.4% retarder +0 ∼ 0.3% dispersant +0 ∼ 0.25% defoamer + water. This new cement system has a good anti-gas channeling performance, the cement strength is 24.5-35.0MPa after 24hrs, the UCA transition time is 16-18min, and the expansion rate is 1.5-1.7%. At the same time, a cementing prepad fluid suitable for the block and the micro-expansion cement slurry system is selected to ensure the performance of the cement slurry's anti-channeling performance. The field test results proofs the good performance of the new cement system. The cementing qualification rate of Koulele W-5 well is 96%, and the second interface cementation is Good. The cementing qualification rate of Trakes CN-1 well is 100% which second interface cementation is Excellent. This paper has positive guidance and reference for cementing in Agadem block.
Dynamic Drilling Fluid Invasion Petrophysical Modeling and Corrections in the Presence of Gas Reservoirs - Arab Formation, UAE
Authors: Portilla Cesar , Moreno Javier 
Published: December 2021

Abstract
Drilling fluid (mud) invasion occurs when the liquid component of the fluid (mud filtrate) invades porous and permeable formations caused by the differential pressure between the wellbore and formation fluids. Changes to the fluid distribution near the wellbore region affects logging tool response, especially those with shallow depths of investigation. The Arab formation in UAE exhibits different degrees of invasion primarily observed in the nuclear and resistivity measurements. This study utilizes tool physics, rock properties, logging time information, and drilling fluid properties, to model invasion corrected log responses and estimate accurate petrophysical properties.
Drilling mud filtrate invasion is observed significantly in all wells drilled in the Arab formation in UAE, affecting both wireline and LWD logging tools. Most of the pilot vertical wells appear to be at residual saturations near the wellbore, where drilling mud filtrate invaded deep into the formation and the radial zones near the wellbore are expected to be completely flushed by the filtrate. Drilling mud invasion in the laterals appears to happen early during the drilling phase affecting LWD tool as well, and the measurement becomes function of the time after drilled, affecting mostly nuclear measurements (density and neutron). Clear understanding of the mud filtrate invasion is required to obtain valid petrophysical interpretations.
To characterize these effects, two invasion indexes are estimated and used as inputs for the petrophysical model. Results are then validated with the use of Nuclear Modeling and Resistivity Inversion by the use of the SNUPAR (McKeon et al, 1988)(Edmundson, H., and Raymer, L.L., 1979)(Wiley, R., and Patchett, J.G., 1990) and UTAPWeLS (Jesus and Carlos, 2009) (Alberto and Carlos, 2010) (Alberto, Carlos and Bill, 2010) (Shaaban, David, and Carlos, 2017) (David, Joaquin and Carlos, 2019). Individual models are created to evaluate pilot vertical wells and horizontal laterals, as well as pure theoretical models are put forward to demonstrate the importance of performing corrections for mud filtrate invasion, showing the differences particularly in the nuclear responses.
Application of Wide-Azimuth Anisotropy Inversion Predicting Carbonate Fracture Intensity and Direction
Authors: Guo Tongcui , Wang Guihai , Song Xinmin , He Dongbo , Zhang Jian , Liu Weiliang , Deng Xili 
Published: December 2021

Abstract
Fractures in carbonate rock are both storing reservoirs and migrating channels for oil and gas, so such fractures are one of the key targets for oil exploration and development. Traditional fracture prediction methods by seismic data include ant tracking cube, coherence cube and other seismic attributes. Fractures predicted by these methods are less accurate. This paper introduces a wide-azimuth anisotropic inversion method to effectively predict the fracture density and direction in carbonates. a wide-azimuth seismic anisotropy inversion workflow is established to predict the fractures in carbonates, and consequently the fractured zones in the target layer. The key steps include: (1) carry out quality control and optimization of wide-azimuth seismic gathers; (2) conduct pre-stack simultaneous inversion of pre-stack seismic data at partial sub-offsets and sub-azimuths to obtain the Vp/Vs of the azimuths; (3) use Azimuthal Fourier Coefficient to calculate the anisotropic gradient and direction. Based on the anisotropic intensity and direction and elastic parameters in the study area, the density and direction of fractures are obtained. The prediction results show that in the study area, nearly SN-striking fractures are developed, which are chiefly tectonic fractures, and consistent with the imaging logging results. It has been proved that the method is reasonable and feasible, and the accuracy of fracture prediction is improved.
A Robust Predictive Machine Learning Model for Supercritical CO2 Foam Strength with Integrated Testing Parameters
Authors: Ahmed Shehzad , Alameri Waleed , Ahmed Waqas Waseem , Hanamertani Alvinda Sri , Khan Sameer Ahmed 
Published: December 2021

Abstract
Unconventional resources have made a significant contribution to fossil energy supply to date, and some specific stimulation techniques have been used in their exploitation. For example, the use of scCO2 foam as a hydraulic fracturing stimulation fluid has sparked considerable interest due to its numerous advantages in terms of fracturing and production performance. The strength of scCO2 foam, an indicator of foam performance, highly depends on the formulation design, foaming properties and operating conditions. Due to complex nature of foam, the quantification of foam strength at downhole conditions is challenging. Specific screening and optimization processes are required to design high performance foam. Although the flow behavior (apparent viscosity) of foam has been extensively studied with empirical models, integrating some essential process parameters into the foam flow behavior evaluation remains challenging. In this study, we present an effective model that incorporates the benefits of a deep learning (DL) approach while taking into account the integration of specific process variables. Several input parameters such as surfactant types and concentration, salinity, polymer concentration, temperature and pressure were used in conjunction with foam quality and shear rate. To predict foam strength while taking the aforementioned parameters into account, a deep neural network (DNN) with optimized hyperparameters was developed. The experimental data for this purpose were obtained using a pressurized foam rheometer. An improved deep learning framework was developed and designed to learn the intrinsic relation among various parameters. The predictive study concludes that, the developed optimized DNN algorithm can provide a reliable and robust prediction with significantly high accuracy. When compared to a shallow network with a standard deviation of less than 5%, the developed optimal deep neural network increased average predictive accuracy to 95.64%. The regression coefficient in the optimized case was found to be nearly one with a low mean square error. The developed DNN algorithm is considered as an improved framework which encompasses several process variables and provides reliable and accurate prediction thus makes it suitable for further integration with fracturing simulator. It would also be helpful for optimizing fracturing process and improving foam formulations.
Improved EOR Polymer Selection Using Field-Flow Fractionation
Authors: Steindl Johannes , Hincapie Rafael Eduardo , Borovina Ante , Puls Christoph , Badstöber Johann , Heinzmann Gerhard , Clemens Torsten 
Published: December 2021

Abstract
Various polyacrylamide polymers have been successfully applied in chemical EOR projects. These polymers are characterised by high molecular weights (MW) to achieve high viscosifying power. The molecular weight distribution (MWD) of the polymers has a major impact on polymer properties and performance. Measuring the molecular weight distribution is challenging using conventional methods. Field-Flow Fractionation (FFF) enables the determination of the distribution to select and quality check various polymers. Polymers with high molar masses (&gt; 1 MDa) are used for EOR to obtain highly viscous aqueous solutions. The MWD of the polymers is crucial for the solution characteristics. Conventional analysis of polymers is performed using either viscometry – which is able to determine the average MW but does not give information on MWD, or size-exclusion chromatography – which is restricted to molecular weights of &lt; 20 MDa. FFF is based on the analytes flowing at different speeds in a channel dependent on their size and mass. This effect leads to separation, which is then used to determine the MWD.
FFF allows to determine the MW and MWD of various ultra-high molecular weight polyacrylamides (HPAAMs). The FFF measurements showed, that despite similar MWs are claimed, substantial differences in MWD are observed. This technology offered the quantification the MWD of HPAAMs up to a MW of 5 GDa. Furthermore, gyration radii of the HPAAM molecules were determined. Selecting polymers on viscosifying power only is not addressing issues related to different MW and MWDs such as selective polymer retention and degradation of the high molar mass part of the distribution. The results were used to improve the polymer selection for chemical EOR projects.
Overall, this work presents a new technique for analysis of ultra-high molecular weight EOR polymers, which enables the possibility to determine the full range of polymer MWD. This available information enhances the EOR polymer selection process addressing selective polymer retention and mechanical degradation in addition to the viscosifying power of polymers.