bluuebunny/crossref_metadata_2025_split huggingface dataset:
Halaqa: preparing a culture of success for young professionals
Authors: Al Kiyumi Hanin Rashid 
Published: December 2021

Abstract
This paper discusses "Halaqa", which aims to create a culture of learning by sharing experiences in sessions where people interact with one another and encouraging the free flow of ideas among the teams. This inspires young professionals to enhance the learning curve, seek new ideas and develop a culture of creative problem-solving pathways.
As a definition, "Halaqa" is a platform for sharing ideas and experiences. The session is planned bi-weekly targeting young professionals in the Petroleum Engineering function. The topic of the session can be presented by (i) a senior or an experienced professional as a part of coaching or (ii) a young professional as a knowledge sharing methodology. The sessions are interactive allowing open discussions for the deeply inquisitive minds. The sessions also provide support with unpacking complex and sticky issues, helping young professionals to replicate the best practices for the efficient and effective delivery of the project. Each session usually takes about an hour including discussions and the points are documented properly for the retention of knowledge.
"Halaqa" is a new concept in the asset and has the potential to be replicated in the entire organization. The uniqueness comes from the fact that it provides a platform to interact and collaborate to pursue common objectives. The relationships that are created through these interactions are crucial as far as the learning of young professionals is concerned.
Risk Based Inspection Study Challenges - An EPC Contractor's Perspective
Authors: Nallamothu Narayana Swamy , Anghel Gelu Dragos , Singh Harendra , Kamal Faris Ragheb 
Published: December 2021

1.0 Abstract
In order to develop an effective inspection program for the early operational phase, Risk Based Inspection (RBI) study is included as a standard requirement in recent EPC Oil & Gas Projects. Conventionally, RBI study was managed by Operators, however nowadays EPC contractors are mandated to execute the same. This paper discusses the challenges faced by EPC Contractor during the execution of RBI study and provides an approach for timely completion of study.
RBI study involves enormous data gathering and risk assessment to identify critical equipment, piping systems to optimize inspection programs and recommends inspection frequencies, locations and techniques. In addition, RBI study covers potential damage mechanisms identification, risk ranking and identification of potential hot spots for development of inspection program.
RBI is normally performed based on risk assessment methodologies derived from International Standards such as API 580/581, DNV RP G101and applicable Operator guidelines. Specialized software is widely used for carrying out integrated activities involving failure probability, consequence assessment and inspection details.
Finally, RBI inspection programs are integrated with Computerized Maintenance Management System.
In order to execute RBI study successfully, a specialized third-party Consultant is normally engaged., Further alignment of all stakeholders including RBI study specialist is essential to address the following: -
Timely availability of "As-built" data for study such as baseline inspection survey reports Agreement on design data versus baseline inspection data for RBI analysis Agreement on appropriate RBI approach: quantitative vs. semi-quantitative/qualitative Acceptance of RBI software Agreement on inspection program recommendations including hot spots, inspection intervals
RBI study activities can be effectively initiated once the equipment fabrication records, piping isometrics, baseline reports and hydro-test data are available. In case of pipelines, inline inspection data should be the initial basis for the pipeline RBI assessment.
EPC contractors normally face following challenges during RBI study execution:
Delay in finalizing the study due to lack of "As-built" data Inconsistency between the outcomes of Corrosion Risk Assessment Study and RBI study performed by third party due to different corrosion modeling software Implications on selected material of construction as a result of RBI Study findings
Ensuring compatibility of RBI templates with Operators CMMS.
NPCC, as a large EPC company, has extensive experience in various Oil & Gas projects where RBI studies are developed in recent EPC projects and ensuring the integrity of the newly constructed assets.
This paper attempts to address the challenges faced by EPC Contractor during execution of RBI studies; emphasizing the strategic considerations to be adopted for successful and timely completion of the study, providing benefits to the End users.
Hybrid Data Driven Approach for Reservoir Production Forecast
Authors: Ourir Achraf , Oukmal Jed , Rondeleux Baptiste , Agharzayeva Zinyat , Barrault Philippe 
Published: December 2021

Abstract
Analytical models, in particular Decline Curve Analysis (DCA) are widely used in the oil and gas industry. However, they are often solely based on production data from the declining wells and do not leverage the other data available in the field e.g. petrophysics at well, completion length, distance to contacts... This paper describes a workflow to quickly build hybrid models for reservoir production forecast based on a mix of classic reservoir methods and machine learning algorithms. This workflow is composed of three main steps applied on a well by well basis. First, we build an object called forecaster which contains the subject matter knowledge. This forecaster can represent parametric functions trained on the well itself or more complex models that learn from a larger data set (production and petrophysics data, synthesis properties). Secondly this forecaster is tested on a subset of production history to qualify it. Finally, the full data set is used to forecast the production profile. It has been applied to all fluids (oil, water, gas, liquid) and revealed particularly useful for fields with large number of wells and long history, as an alternative to classical simulations when grid models are too complex or difficult to history match. Two use cases from conventional and unconventional fields will be presented in which this workflow helped quickly generate robust forecast for existing wells (declining or non-declining) and new wells.
This workflow brings the technology, structure and measurability of Data Science to Reservoir Engineering. It enables the application of the state of the art data science methods to solve concrete reservoir engineering problems. In addition, forecast results can be confronted to historical data using what we call "Blind Testing" which allows a quantification of the forecast uncertainty and avoid biases. Finally, the automated workflow has been used to generate a range of possible realizations and allows the quantification the uncertainty associated with the models.
High Resolution Reservoir Simulator Driven Custom Scripts as the Enabler for Solving Reservoir to Surface Network Coupling Challenges
Authors: Aktassov Kanat , Ayaganov Dauletbek , Imagambetov Kanat , Alissov Ruslan , Muratbekov Said , Kali Zhaksylyk , Amangaliyev Bagdad , Sidorov Dmitry , Kurmankulov Alikhan 
Published: December 2021

Abstract
This paper presents a practical methodology of optimizing and building a detailed field surface network system by using the high-resolution reservoir simulator driven custom-made Python scripts to efficiently predict the future performance of the vast oil and gas-condensate carbonate field.
All existing surface hydraulic tables are quality checked and lifting issue constraints corrected. Pressure losses at the wellhead chokes incorporated into the high-resolution reservoir simulator in the form of equation by using the custom scripts instead of a table format to calculate gas rate dependent pressure losses more precisely. Consequently, all 400+ surface production system manifolds, pipes and well chokes Horizontal Flow Performance (HFP) tables are updated and coupled to the reservoir simulator through Field Management (FM) controller which in turn generates Inflow Performance Relationship (IPR) tables for the coupled wells and passes them to solve the network.
The methodology described in this paper applied for a complex field development planning of the Karachaganak. At present, reservoir management strategy requires constant balancing effort to uniformly spread gas re-injection into the lower Voidage Replacement Ratio areas in the Upper Gas-Condensate part of the reservoir due to reservoir heterogeneity. Additionally, an increase in field and wells gas-oil ratio and water-cut creates bottlenecks in the surface gathering system and requires robust solutions to decongest the surface network.
Current simulation tools are not always effective due longer run times and simulation instability due to complex network system. As a solution, project-specific network balancing challenges are resolved by incorporating custom-made scripts into the high-resolution simulator. Faster and flexible integrated model based on hydraulic tables reproduced the historical pressure losses of the surface pipelines at similar resolution and generated accurate prediction profiles in a twice-quicker time than existing reservoir simulator. Overall, this approach helped to generate more stable production profiles by identifying bottlenecks in the surface network and evaluate future projects with more confidence by achieving a significant CAPEX cost savings.
The comprehensive guidelines provided in this paper can aid reservoir modeling by setting up flexible integrated models to account for surface network effects. The value of incorporating Python scripts demonstrated to implement non-standard and project specific network balancing solutions leveraging on the flexibility and the openness of the modelling tool.
Successful Development of Residual Gas Condensate Reservoir using First ESP in Deep High Pressure and Temperature in Rich Gas Condensate Wells
Authors: Shuely Abdullah Salim , Sheibani Hilal , Al Lawati Hawraa , Ezechie Patrick , van Gilst Roeland , Siyabi Nabil , Al Kharusi Dawood , Marhoon Nadhal , Al Otani Louisa , Lawati Taha 
Published: December 2021

Abstract
A rich condensate gas field is located in the North of Oman, which penetrated the Amin sandstone reservoir at 4015 TVDmss. A study was conducted in the field and showed there is ¾ of GIIP trapped with paleo imbibition - over geological time - gas by the water encroachment in an approximately 80 m thick Paleo-Residual Gas zone (PRG), with very low mobility of hydrocarbons and high residual gas saturations.
In order to mitigate the shortcomings of such unfavorable subsurface conditions, the study proposed Gas-Aquifer-Rate Management (i.e. co-production of gas and water) utilizing existing flank wells, as a potential field improvement option. The key business drivers for this project are to re-mobilize gas from PRG flank wells and to safeguard existing NFA by Aquifer pump off and production from high rate crestal wells.
The optimum gas well deliquification method has been identified based on the highest UR considering connected GIIP and well completion size. The outcome of the study indicated that the ESP technology combined with well retubing was recommended as the optimum solution. Two wells have been selected as ESP candidates to test the new technology to produce water at deep depth (4000m) and high temperature (155°C). A special slim ESP was designed for this purpose.
A successful pilot was completed in one well and gave conclusive results. The test showed that the well produced 3K m3/d of gas and 83 m3/d of liquid with 95% BSW. The second pilot is currently in the commissioning phase. The successful outcomes of the pilot succeeding in connecting the gas and restoring wells back with economic production rates will lead to expedite a full field implementation plan. This project will add a significant economic value of positive NPV at low UTC.
This paper will highlight the full story of the PRG and ESP technology implementation and describe in details the entire process starting from the artificial lift selection, well candidate selection screening criteria, critical success factors, operating parameters, life-time cycle and the test results of gas and condensate and water production. Also, the learning and challenges in operating the ESP will be shared.
A Logic-Based Risk Engineering Approach to Support the Decision-Making Process of Upstream Projects
Authors: Vimercati Roberto , Fratoni Filippo , Comploi Karin , Petralia Mirko , Corvi Filippo , Ciotola Angela , Colombo Simone 
Published: December 2021

Abstract
The exploration and production of hydrocarbons is undeniably a high-risk venture. Uncertainties are in every activity, from the exploration phase up to facilities construction and plants operation.
To allow decision makers understanding the uncertainty associated with the decisions they were asked to face, in the 70ies of the past century, when the oil shockwaves upset the entire business world (Bood & Postma, 1997), it was introduced the use of scenario analysis. Since then, stochastic analyses, such as Monte Carlo simulations, started permeating the oil & gas world. Yet, as Lewis et al. (2004) highlighted, despite the benefit greatly outweighs the effort generally required to perform these analyses, managers not seldom refrained themselves from using these tools to support their decision-making processes. And this, as highlighted by Judah (2016), despite risk mitigation is the very core of the oil & gas business as risks at stake are many, namely: drilling risk, subsurface risk, cost & schedule risk, procurement risk, performance risk, health, safety, and environment (HSE) risk, geopolitical risk, and price risk.
Today, the energy transition is imposing new challenges to the oil & gas sector. Even amongst those companies that have embraced (quantitative) structured approaches to support their investment decisions, there is another challenge to face: the integration of all risks in one approach capable of capturing the overall complexity of oil & gas projects and highlighting the effects of variations of both endogenous and exogenous risks on the overall profitability of the opportunity at stake (or the portfolio of opportunities). Risks are typically assessed separately by each function with different quantitative approaches that leave grey zones of interpretation where inter-functional risks can grow and create decisional inefficiencies. Aware of this, Eni integrated risk management, started last year a project aimed at enhancing the project risk management process. The innovative approach followed leverages on artificial logic and allows to consider the full life cycle of an investment proposal. In line with the evolution of company's mission and vision, the aim was to assess the project risk in a more comprehensive way by considering endogenous risks (such as permits, drilling, engineering, procurement, construction) jointly with exogenous ones (such as climate change, cyber security, credit, and country). The manuscript explains the methodology used, the results achieved, and the expected benefit for the company in adopting the innovative approach to risk engineering in supporting investments decisions.
Company Data Governance Transformation to Support the Business Evolution
Authors: Sanasi Carla , Dal Forno Luca , Ricci Maccarini Giorgio , Mutidieri Luigi , Tempone Pamela , Mezzapesa Domenico , Dalla Rosa Matilde , Bucci Alessandro , Rinaldi Francesca , Andreoletti Clara 
Published: December 2021

Abstract
The evolution of the energy market requires companies to increase their operating efficiency, leveraging on collaborative environment and existing assets, including Data. A new focus on data governance and integration is needed to maximize the value of data and ensure "real-time" efficient response.
The decoupling of data from applications enables organization by domain and data type in one cross-functional data hub. This scheme is independent from the scope of the activity and will therefore maintain its validity when dealing with new business requiring subsurface data utilization. The integrated data platform will feed advanced digital tools capable to control the risks, optimize performance and reduce emissions associated with the operations.
Eni is putting this idea into practice with a new data infrastructure which is integrated across all the subsurface disciplines (G&G, Exploration, Upstream Laboratories, Reservoir and Well Operations departments). In this paper, the example of real time data exploitation will be discussed.
Real time data workflow was first established in well operations for operational supervision and later developed for real time performance optimization, through the introduction of predictive analytics. Its latest evolution in the broader subsurface domain encompasses the application of AI to operations geology processes and the extension to all operated activities. This approach will equally support new company goals, such as decarbonization, increasing performance of subsurface activities related to underground storage of CO2 in depleted reservoirs.
Large Scale Reservoir Simulation Models for Regional Understanding of Inter-Field Communications - A Case Study Offshore Abu Dhabi
Authors: Parra Humberto , Mogensen Kristian , Alobeidli Abdulla 
Published: December 2021

Abstract
Reservoir simulation models aim to reproduce at well, sector and field level the pressure and production behavior observed in the historical data. The size and resolution of the models are essentially capped by the computational resources as the numerical computations are quite complex and hardware demanding. For this reason, the use of simulation models to understand inter-field communications at regional level have been always a challenge, rarely pursued, referring those analyses to simple material balance to evaluate influxes, lacking lateral vectors to identify where volumes are coming from, especially on cases of multiple field interactions. The work presented in this paper illustrates the value of merging existing field level simulations models into a large scale regional simulation grids, in order to understand pressure disturbances observed in multiple fields Offshore Abu Dhabi.
The process of merging simulation models represents a big challenge considering the high variety of approaches used in the original models, different geology complexity, fluid characteristics, different depletion regimes and field development strategies. In this study, thousands of wells, 6 structures with different fluid and equilibrium regions were used to build the biggest reservoir simulation model in Abu Dhabi. The integration of the data pursues the replication of the existing static and dynamic models, addressing in parallel lateral and vertical upscaling issues when moving from very fine into coarser grids. Implications on the change of scale on the repeatability of the HCIIP volumes and the impact of pseudo relative permeability curves on the history match were carefully analyzed during the process. Evaluation of the impact of the simplifications over the overall quality of the model was of paramount importance, interrogating whether the simplifications affects the capability of the model for assessing the pressure communication and influxes among the fields.
The regional simulation model allowed to understand the effects of the peripheral water injection of a giant field on the nearby satellite fields, also the effects of these interactions on the pressure and oil saturation changes through time. Fields and Structures separated way far (20 and 40 Km away) can eventually see pressure disturbances after very long periods of time (up to 300 psi in couple of decades in some cases). Although evidences for changes in pressure are very clear and supported by RFT/MDT time lapsed data, the work also proved that changes on saturations are not very evident or can be considered very marginal on fields separated by large distances.
This work represents an alternative and more accurate approach for evaluating nearby field communications and to quantify the boundary conditions to restore models at original stage before nearby interferences, allowing proper initialization of the fine scaled simulation models on pre-production status.
Overcoming Production Logging Challenges in Evaluating Extended Reach Horizontal Wells with Advanced Completions
Authors: Younis Akram , Alshehhi Mohammed , Al Braik Haitham , Uematsu Hiroshi , El-Sayed Mohamed , Manzar Muhammad Abrar , Ismail Mostafa , More Manjiri 
Published: December 2021

Abstract

Objective/ Scope
Production logging analysis is essential to understand and evaluate reservoir performance throughout the lifetime of an oil well. Data acquisition and analysis is known to be challenging in modern extended reach horizontal wells due to multiple factors such as conveyance difficulties, fluid segregation, debris, or open hole washouts. Advanced compact multiple array production logging tool (APLT) is proposed to minimize the uncertainties related to these challenges.

Method, Procedure, and Process
The proposed sensor deployment method provides a comprehensive borehole coverage, thus maximizing the amount of subsurface information collected to evaluate the production performance of a horizontal well. Essential measurements are combined on six individual arms. Each arm is independently deployed which guarantees the best borehole coverage in a variety of borehole condition. Robust mechanical arm design minimizes damage, allows tolerance to decentralization, and provides greater confidence in determining the sensor locations. Each arm utilizes two fluid holdup sensors (Resistance, Optical) and one velocity sensor (Micro-Spinner). Co-location of the sensors minimizes the uncertainty related to sensor spacing when compared with previous generation of APLT.

Results, Observations, Conclusions
The new sensor deployment method and analysis results are discussed showing the added value in barefoot completion as well as advanced ICD completion. The holdup sensors response from previous generation APLT is compared to the advanced tool and how it relates to better borehole coverage. The results also illustrate use of high frequency optical probes for phase holdup determination. In addition, the optical probes are used to confirm bubble point pressure at in situ conditions by confidently detecting the first gas indication in the tubular. The results clearly show how a compact APLT maximizes the borehole coverage in highly deviated and horizontal wells. This is critical in collecting representative data of all segregated fluids which enables more accurate interpretation of the flow profile in the well and better understanding of reservoir performance.

Novel / Additive Information
The novelty of the new instrument is the ability to maximize the amount of subsurface production logging information collected with low uncertainty and minimum operational risk.