bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Risk Based Maintenance Optimization RBMO to Save Costs
Authors: Mohamed Khaled Ahmed Farouk 
Published: December 2021

Abstract
Maintenance is a crucial pillar in plant integrity and availability. Saving money in maintenance should be established without affecting the asset's integrity. Based on this, the core of work is to maximize the maintenance return on investment (ROI). Maintenance ROI is the ratio between invested money in maintenance to mitigated risks due to maintenance actions. The objective is to minimize maintenance cost while maximizing assets integrity and availability.
RBMO starts with ‘Maintenance Criticality Assessment’ (MCA) at unit/system level to define high (20 % of systems that represent 80% of risks), medium (20% of systems that represent 15% of risks), and low critical systems (60% of systems that represent only 5% of risks). Based on system criticality, a dedicated risk assessment is implemented to evaluate risks at tag level to define the worst maintenance action/s.
High critical systems’ maintenance programs are developed using ‘Reliability-Centered Maintenance’ (RCM). Medium critical system maintenance program is developed using ‘Failure Mode, Effects and criticality analysis’ (FMECA). "Maintenance strategy for Low Critical item" guideline document is developed to define the best maintenance strategy for low critical units.
All risks are evaluated using the standard ADNOC risk matrix. The risk is converted to monetary value in $ to evaluate maintenance actions using a formula.
A special program was developed to facilitate MCA evaluation for each system and represent risk as monetary value using ADNOC Risk Matrix taking into consideration the redundancy and demand on a system during operation. MCAs were completed for all ADNOC Onshore Assets, see results below. Optimization starts by evaluating maintenance programs for low critical systems to save costs where low critical systems represent 50% to 60% of total systems in ADNOC Onshore. Based on this the total number of work orders has decreased by 6856, which is equivalent to saving $1M annually.
In parallel, RCMs are conducted on high critical systems. Risk mitigation calculator in $ value was developed and embedded in the RCM information sheet to calculate cost benefit from implementing maintenance programs that were developed.
RBMO is a systematic and traceable methodology to minimize maintenance cost and at the same time maximize system integrity and availability.
This work showed the importance of reviewing the low critical systems’ maintenance program, as a first step in RBMO after implementing MCA, where low critical systems represent 50% to 60% of total assets and only 5% of total risks. ADNOC Onshore developed a dedicated guideline document "Maintenance Strategy for Low Critical Item" to facilitate decision making for proper maintenance strategy for low critical systems. Adding RCM risk mitigation calculator to RCM to calculate RCM cost benefit.
Offshore Structure Specific Performance Targets
Authors: Atia Mohamed , Abdelkhalek Ahmed , Sarkar Anjan , Keys Matt , Patel Mahesh , Eissa Mohamed , Omar Tarek 
Published: December 2021

Abstract
Offshore structures exist in the harshest environments and each region is unique in the severity and development of extreme weathers. This had led to challenges in the identification of a single criterion that's internationally applicable. ADNOC Offshore and Kent, formerly Atkins Oil and Gas, worked closely in 2010 to develop a high-level generalised regional criterion for the Arabian Gulf and in 2020, a major project was conducted to develop a structure-specific criterion that resulted in considerable improvement in risk levels and financial gains.
For each of ADNOC Offshore's 480 structures, a Response Based Metocean Analysis (RBMA) was conducted adopting Tromans and Vanderschuren (1995) approach. Structure specific hindcast data at 3-hour intervals over a period of 37 years was analysed, isolating storms and executing hydrodynamic analyses considering joint environmental conditions. Through adopting a combination of peak-over-threshold method and Markov-Chain-Monte-Carlo (MCMC) simulations, convolution of long-term (storms) and short-term (wave probabilities within a storm) was conducted resulting in the generation of the Hazard Curves that account for the possible uncertainties associated with variations in each of the distributions.
The structure specific response based metocean analysis resulted in a considerable improvement in the criteria for ADNOC Offshore’s structures. The resulting Hazard Curve ratios (10,000-year to 100-year response parameter ratio) for approximately 95% of the structures were evaluated lower as compared to the 2010 generalised study. It was observed that the water current profiles had a significant impact on the hazard ratios, and specially for assets in the vicinity of the islands. Based on the resulting hazard ratios a detailed risk assessment was conducted and compliance and life extension of most of ADNOC Offshore structures was justified without the need for physical strengthening of their assets.
Through the use of machine-learning algorithms associated with serval statistical sampling techniques, extreme value analysis was conducted in conjunction with the MCMC approach and resulted in what is likely to be the largest offshore fleet application of the method.
Bulk Rheology and Injectivity Assessments of Potential Biopolymer and Synthetic Polymer for Applications in Carbonates Under Harsh Conditions
Authors: Elhossary Deena A. , Sebastian Anoo , Alameri Waleed , Al-Shalabi Emad W. 
Published: December 2021

Abstract
Polymer flooding is a well-established chemical EOR technology that is used to overcome challenges associated with conventional waterflooding including viscous fingering and early breakthrough. Nevertheless, polymers tend to perform poorly under harsh reservoir conditions of high temperature and high salinity (HTHS). The main objective of this study is to evaluate and compare the performance of two potential polymers, an ATBS-based polymer and a biopolymer (Scleroglucan), in carbonates under harsh reservoir conditions. This comparative study includes an analysis of polymer rheological experiments as well as polymer injectivity tests. The effects of water salinity and temperature on the performance of these two polymers was also investigated in this study. Rheological experiments were carried out on polymer samples at both ambient (25 °C) and high temperature conditions (90 °C). Polymer viscosity was measured as function of concentration, temperature, and salinity at different shear rates ranging from 1 to 1000 s−1. Injectivity characteristics of both polymers were also assessed through coreflooding experiments using high permeability carbonate outcrops at room (25 °C) and high (90 °C) temperature conditions. The injectivity tests included two stages of brine pre-flush and polymer injection, which allowed assessing the resistance factor (RF) of these polymers. These tests were conducted using high salinity formation water (167,114 ppm TDS) at both temperature conditions.
The bulk rheological tests showed that both ATBS-based and Scleroglucan polymers exhibit a shear-thinning behavior. However, the shear-thinning effect is far more evident at higher concentrations in the case of Scleroglucan as opposed to that of the ATBS-based polymer. Viscosity measurements of the polymer samples at different salinities demonstrated the detrimental impact of salinity and divalent ions on the stability of ATBS-based whereas Scleroglucan was not much affected. Scleroglucan exhibited better filterability at the high temperature as opposed to the room temperature. From the injectivity tests, the shear-thinning behavior of the biopolymer in the porous media was confirmed as RF decreased with increasing the flow rate applied at both temperature conditions. Meanwhile, the ATBS-based polymer exhibited a shear-thickening behavior at 25 °C, but a shear-thinning one at 90 °C. Compared to the biopolymer, the ATBS-based polymer showed better injectivity at both the room and the high temperatures as the differential pressure stabilized within the first few pore volumes injected. This study highlights the importance of polymer screening for EOR applications in carbonate reservoirs under HTHS conditions.
A Study of Seepage Characteristics of Unsteady Waterflooding Development for Fractured Ultra-Low-Permeability Reservoir
Authors: Liu Qing , Li Xiangfang , Yang Jian , Feng Sen , He Minxia , Fang Yongjun 
Published: December 2021

Abstract
Unconventional fractured ultra-low-permeability reservoirs play an important role in continental sedimentary basins in China, and their formation characteristics and seepage laws are greatly different from that of traditional reservoirs. In this paper, the influence of microfractures and unsteady waterflooding on the productivity of fractured ultra-low permeability reservoirs are studied deeply. The reservoir parameters used in the study are from an actual fractured ultra-low-permeability reservoir in Ordos Basin, where microfractures are developed but macroscopic fractures are not. The microfractures have a small opening and are widely distributed in the reservoir, so the reservoir numerical simulation model adopts the equivalent continuous matrix model to simulate waterflooding. On one hand, the physical model of micro-fractured reservoir and the permeability tensor model of the equivalent continuous matrix are established. The results show that the existence of microfractures can increase the permeability of matrix by 1.4 times. On the other hand, an ideal heterogeneous numerical simulation model composed of pure matrix and equivalent continuous matrix considering microfracture is established according to actual geological parameters of the fractured ultra-low-permeability reservoir. To simulate and compare the unsteady waterflooding and continuous waterflooding development in 10-year development under the condition of constant annual injection rate, the results indicate that unsteady waterflooding development make higher productivity and lower water cut and lower formation water saturation than that of continuous waterflooding. By conducting unsteady waterflooding development simulation for sensitivity analysis, the results demonstrate that the greater the capillary force, the better the role of capillary imbibition in a certain range, meanwhile, the unsteady waterflooding has the best exploitation effect when the value of water injection cycle time is 100 days and the fluctuation amplitude of water injection rate is 1. At the above situation, the displacement and capillary imbibition and pressure disturbance achieve the desired effect of reducing water cut and increasing oil production.
Improving Long-Term Hydraulic Fracture Conductivity in Carbonate Formations by Substitution of Harder Minerals
Authors: Samarkin Yevgeniy , Aljawad Murtada Saleh , Amao Abduljamiu Olalekan , Sølling Theis Ivan , Al-Ramadan Khalid , AlTammar Murtadha J. , Alruwaili Khalid M. 
Published: December 2021

Abstract
Hydraulic fracturing is applied in tight formations to create conductive paths within the reservoir. However, the conductivity of the created fractures declines with time due to the closure stresses. The decline is sharp in soft formations because of proppant embedment and fracture surface asperities failure. The improvement in fracture surface hardness can mitigate the abovementioned challenges and sustain the fracture conductivity. This research targeted enhancing carbonate rock's hardness by forming minerals harder than calcite.
Carbonate rocks, namely dolomite, limestone, and chalk, were treated at ambient temperature conditions by immersion into the aqueous solutions of NaF and ZnSO4 with a concentration of 0.1M. During treatment, the solution was sampled to monitor the changes in ion concentration and estimate the reaction kinetics by ICP - OES and IC devices. The hardness of rock samples was measured by impulse hammering technique before and after the treatment. The changes in rock's mineralogy and elemental content were studied by XRD and SEM imaging. The permeability of rocks was estimated by the steady-state gas injection method.
The formation of smithsonite (ZnCO3, Mohs scale hardness - 4.5) and fluorite (CaF2, Mohs scale hardness - 4) was achieved in the reaction of calcite (CaCO3, Mohs scale hardness – 3) with ZnSO4 and NaF, respectively. Chalk and limestone reacted efficiently with both solutions; however, the dolomite reaction with solutions was feeble. XRD detected the newly formed smithsonite minerals, and it was observed in SEM images that minerals formed an interconnected net in chalk and limestone specimens. In dolomite samples, the minerals formed isolated gatherings that were sparsely located on the grains. The treatments caused the improvement of the rock specimen's hardness. 0.1M solution of NaF was not effective in strengthening the rock samples (only chalk sample experienced 6.7% improvement in hardness) because of low concentration of the solutions used; however, treatment resulted in negligible changes in permeability of the samples. In contrast, Young's modulus of limestone and chalk treated by ZnSO4 increased by 17% and 21%. Permeability of rocks treated by ZnSO4 reduced drastically, most likely due to the formation of gypsum as a byproduct of the reaction.
This research presents a method for carbonate rock hardening via the transformation of parent calcite into harder minerals. It explains its possible application in the petroleum industry to sustain the conductivity of propped/acid fractures. The proposed technique will help to mitigate fracture conductivity decline due to proppant embedment and asperities failure issues that are especially severe in soft formations.
The World's First Offshore GASWAG EOR Full Field Implementation
Authors: Khanifar Ahmad , Bin Subari Ibrahim , Bin Abd Raub Mohd Razib , Deo Tewari Raj , Bin Sedaralit Mohd Faizal 
Published: December 2021

Abstract
A major matured Malaysian offshore oilfield with more than 40 years of production history under a combination of moderate to strong aquifer support and moderate-size gas cap will be subjected to a unique enhanced oil recovery (EOR) scheme, the first of its kind offshore, called Gravity Assisted Simultaneous Water Alternating Gas (GASWAG) injection process. It is essentially a scheme which involves simultaneously injection of gas and water which involves injecting water up-dip and gas down-dip structurally in a depleted oil reservoir. This method takes the advantage of gravity drainage mechanism to maximize recovery from un-swept oil zones down-dip by aquifer influx and up-dip by gas cap expansion processes and it could be different than the conventional water alternating gas (WAG) method.
This paper mostly presents the dynamic modelling and simulation work which has been established during this case study to obtain the GASWAG base case model and to conduct the optimization and sensitivity assessments on the major reservoir parameters. It also describes the main subsurface uncertainties and operational risks and their impact on incremental oil reserve and the results were used to design mitigation plans to help minimize impact on oil recovery volumes. Implementing the full field scale of this EOR scheme involves a detailed reservoir management plan (RMP) with many reactivations of idle wells, well workover plans, behind casing opportunities and adding perforation interval together with identified new infill wells to maximize the flood-front movement of the injected fluids. Obviously, good communication with field operational personnel is paramount to ensure these RMP are adhered to clear targets to successfully achieve the desired incremental recovery and will be elaborated in this paper.
This paper describes the strategy and workflow to monitor and measure the two key success factors of this project which are production attainability and reserve attainability. The success of this project depends on continuous evaluation to check the actual performance against the anticipated behavior. As soon as new information obtains along implementation, it will be assessed against targets to steer the way to the main goal of additional reserve by the end of field life. Thus, it requires a comprehensive monitoring plan with detailed surveillance and data collection and, well testing to revisit and update the dynamic model accordingly.
The results of this study show that GASWAG has emerged to be one of the most promising techniques with the highest incremental reserve for this field among various EOR techniques evaluated such as continuous gas injection, continuous water injection, conventional WAG, aquifer-assisted WAG, and double displacement.
Inventory Verification in Underground Gas Storage Rebuilt from Depleted Gas Reservoir: A Case Study from China
Authors: Song Lina , Xu Hongcheng , Wanyan Qiqi , Liao Wei , Zhang Shijie , Shi Lei , Zhao Kai 
Published: December 2021

Abstract
Inventory verification is one of vital tasks in underground gas storage (UGS) management process. For one reason, it is possible to know exactly how much natural gas is actually in the gas storage and ensure that it can be produced and supplied to the market in winter season when needed. For another, possible natural gas leakage can be discovered in time by inventory verification, to ensure the safe and economic operation of the gas storage. HTB UGS is a gas storage facility rebuilt from a depleted gas reservoir in China, which has been commissioning in June 2013. After 7 years injection-withdrawal cycles, we calculated and analyzed the inventory of this gas storage.
First and foremost, we analyzed the data of 13 observation wells, including monitoring of gas-water interface, caprocks, and faults of the HTB UGS. In addition, we carried out core experiments in the laboratory to simulate the multi-cycle injection and withdrawal of gas storage, and analyzed the microscopic pore seepage characteristics of the reservoir during the UGS operation. Next, based on the operating pressure test data of the gas storage, we corrected the formation pressure and calculated the effective inventory. Furthermore, combined with the simulation results that we have carried out in the previous period, the effective inventory of HTB UGS was comprehensively evaluated.
The result shows that: 1) The complete monitoring system indicates that the HTB UGS has no gas escaping from the storage field through faults, caprocks or wellbore. 2) The experimental result shows that in the process of gas withdrawal, various forms of natural gas such as jams and bypasses in some areas of the reservoir cannot participate in the flow, leading to this part of natural gas cannot be used. 3) Inventory calculation shows that as of the end of gas withdrawal in March 2020, the book inventory of HTB UGS is 99.8×108m3，while the effective inventory is 91.8×108m3 and the working gas is 39.9×108m3. 4) By acidification or other measures to improve the geological conditions, intensifying the well pattern and extending the gas production time, HTB UGS can increase its effective inventory.
With the great efforts in constructing underground gas storage in China and the market-oriented operation of UGS, inventory verification of gas storage will become increasingly important. The inventory analysis method established in this article can provide a certain reference.
IR 4.0 Technologies Enable Breakthroughs in Upstream Production Operations
Authors: Al-Hajri Nasser M. , Ureiga Sulaiman T. , Barghouti Akram R. , Gilani Syed K. , Javed Muhammad Imran 
Published: December 2021

Abstract
The fourth industrial revolution (IR 4.0) has brought about many exciting and game changing technological advancements in recent years that span across different industries. Our petroleum industry was no exception. In this paper, we will present realizations of IR 4.0's fruitful impact on multiple upstream production engineering and operation problems.
The first IR 4.0 technology uses machine learning techniques to predict scale inhibition and design inhibition programs that arrest scale formation. Scale formation is a common oilfield problem that consumes a lot of expense from operators. The machine learning method has shown its ability to curtail such expenses and manage risks associated with scale formation. The second technology is modeling the reliability of downhole Inflow Control Valves (ICVs) and predicting their failure. The technology is based on advanced big data analytics and uses automated statistical techniques to achieve the method objectives. This technology provides production engineers with an analytical decision-making model to predict ICVs failures and suggest the optimum frequency for stroking or cycling of the downhole valves as a preventive maintenance practice. The third IR 4.0 technology is the automated well integrity risk ranking. This particular technology uses smart interfaces and advanced computation algorithms applied on big data to assign (or weigh) risks of a well in terms of well integrity. This intelligent integrity ranking or classification shifts focus to wells prone to integrity failures more than the healthy ones. In addition, the method helps optimize integrity surveillance resources and prevents the obvious setbacks from a well integrity issue.
The paper will explain detailed methodologies of all three IR 4.0 technologies and outline expected results from field implementation of those technologies.
Automation of Carbonate Rock Thin Section Description Using Cognitive Image Recognition
Authors: Shebl Hesham Talaat , Al Tamimi Mohamed Ali , Boyd Douglas Alexander , Nehaid Hani Abdulla 
Published: December 2021

Abstract
Simulation Engineers and Geomodelers rely on reservoir rock geological descriptions to help identify baffles, barriers and pathways to fluid flow critical to accurate reservoir performance predictions. Part of the reservoir modelling process involves Petrographers laboriously describing rock thin sections to interpret the depositional environment and diagenetic processes controlling rock quality, which along with pressure differences, controls fluid movement and influences ultimate oil recovery. Supervised Machine Learning and a rock fabric labelled data set was used to train a neural net to recognize Modified Durham classification reservoir rock thin section images and their individual components (fossils and pore types) plus predict rock quality. The image recognition program's accuracy was tested on an unseen thin section image database.