bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-Simulation Enhanced Oil Recovery Technique Screening in X and Y Fields Using a Combination of Analytical Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution
Authors: Priadi Sunni Nugraha , Ismoyo Hadi , Wahjudewanti Alexandra Sinta 
Published: September 2021

Abstract
The X and Y fields are among the oil fields in the Java basin, Indonesia. As oil production decreases due to exploitation activities in X and Y fields, it is necessary to carry out activities to increase production. To increase the yield of its oil production, Enhanced Oil Recovery (EOR) technology is needed. Enhanced oil recovery (EOR) technique screening analysis is needed to be carried out at the initial stage of the feasibility study in the EOR project. At present, there is no fully established method for identifying potential candidates for the EOR technique. The most common approach for selecting EOR techniques is conventional filtering, which is generally based on the "go-no go" trial and error, with a reduced chance of success. Besides, determining potential candidates for EOR techniques often uses a reservoirsimulation approach, but this is time-consuming and requires high costs in using the software license. EOR technique screening with a method that explains how to form a multi-criteria decision-making model with a combination of AHP and TOPSIS methods together as a systematic and measurable method to get the best EOR techniques in both X and Y fields.
The research results found that the CO2Immiscible Technique was the most appropriate for EOR in fields X and Y because it has the highest preference value (0.676), is then followed by the Micellar technique (preference value 0.645) and HC Immiscible (preference value 0.517). With the multi-criteria decision-making technique, the best EOR technique results are obtained.
Then the proposal can provide valuable recommendations for company management in both fields X and Y with a faster, accurate, and inexpensive method compared to the reservoir simulation method, which has a longer processing time and more expensive costs. This technique can support technology implementation decision-making in the early stages of EOR project development.
Business-Oriented Reserves and Resource Management - Experiences from a Merger
Authors: Dose Thies , Kachel Gunar 
Published: September 2021

Abstract
In May 2019, the merger between Wintershall GmbH and DEA Deutsche Erdoel AG was closed, which was the start of Wintershall Dea.This paper provides detailed insight into managing reserves and resource information during this merger.
After merger, three resource management activities required attention: (i) combining existing resources reporting, (ii) defining a lean but effective resources management and control system, and (iii) ensuring readiness for Initial Public Offering (IPO) by establishing an external independent evaluation of resources ("external resource audit"). This paper describes objectives, challenges and solutions on reserves and resources reporting of the new company.
The merged reserves and resources database of the previous year's reports had to consider audits from two different reporting systems in parallel to four different external auditors.With priorities defined by status of external auditing, operatorship and asset share a common database was derived and could immediately be used for financial transactions such as the issuance of an inaugural bond.
The new system for internal reporting of petroleum resources provides a fit-for-purpose approach, such as a consistent interpretation of commerciality criteria or definition of resources sub-classes.Particular attention was paid to synergies with respect to business planning, strategic portfolio analysis, and a link to technology & innovation. By defining specific attributes and sub-processes, the portfolio can be analyzed systematically. This provides additional insights and ensures synergies with business planning, strategic planning as well as internal technology initiatives.
A systematic resource control system is defined focusing on internal review, external and internal audits as well as synergetic use of project reviews. Moreover, a feedback loop for continuous improvement of reservoir management allows attending to important audit observations.
The external resource audit to ensure IPO readiness was structured to assign tasks for head office, business units and auditing company.The sequence of events from introduction to assets to reconciliation of differences between auditor and company was set-up, executed and monitored.Focus was on the definition of a structured but agile approach for external independent evaluation of all reserves and contingent resources.
Demystifying Openhole and Outer Casing Geometry and Annulus Material Characterization with Third Interface Echo TIE Response
Authors: Kumar Apoorva , Agrawal Gaurav , Singh Kamaljeet , Kumar Nitesh , Dutta Shaktim 
Published: September 2021

Abstract
Ultrasonic imaging based tools have been used for long for delivering high-resolution, comprehensive real-time confirmation of the pipe-to-cement bond quality and downhole pipe condition. However, for comprehensive analysis of cement barriers in challenging scenarios like lightweight cement and for better distinction between different annular materials downhole, a multi-physics evaluation has been developed which combines the measurements taken in thickness-mode with measurements taken in flexural-mode of the casing. Signals from these independent measurements are then processed to provide robust interpretation of solid-liquid-gas behind casing using acquired flexural attenuation and acoustic impedance data.
The information provided by the flexural attenuation is related to the state of the material in contact with the casing and does not probe deeper into the cement sheath. However, the pulse radiated by the flexural wave packet into the annulus may be reflected by the third interface, the interface with the formation or outer casing. The inner casing is fairly transparent to this reflected pulse so that it can also be picked by the receivers with significant amplitude. Since this reflected pulse propagate through the thickness of the annulus layer it may bring valuable information about the annulus geometry and material, and about the formation or outer casing geometry.
This paper demonstrates third interface echo principles and showcases several case studies for evaluating the outer casing geometry, annular material characterization, casing cut and pull depth suggestion and determining open hole size.
World First Commercial Application of Permanent Interventionless Monitoring Using Intelligent Inflow Gas Tracer Technology
Authors: Abdul Aziz Khairil Faiz , Mustafa Azreen , Wong Paul , Wurtz Marie , Leung Edmund , Overby Landrø Ståle , Koumouris Steve 
Published: September 2021

Abstract
Over the past decade, commercially available inflow tracers have been increasingly used to permanently monitor lower completions without the need for intervention. They have been designed to release selectively to oil or water, typically for clean-up verification, inflow quantification and identifying the location of water breakthrough in oil reservoirs.
Naturally, there has been an industry demand and requirement to develop inflow gas tracers to monitor gas reservoirs and identifying the location of gas breakthrough in oil reservoirs. In a green field development, it is important to obtain as much measurements as possible to understand completion efficiency and guide reservoir management decisions.
This paper presents the first commercial installation of inflow gas tracer technology that has been deployed in a dry gas field by HESS Malaysia in open hole stand-alone screen completions. It discusses the original monitoring objectives of this application in a full field development and how they evolved due to the gas tracer capabilities and the need for early well and field information. This paper will also discuss the retrofit screen design that allowed the gas tracers embedded in a polymer matrix called gas systems (GS) to be installed inside premium mesh screens.
At the wellsite, sampling campaign adjustments were executed depending on the flowing conditions during the clean-up, restarts to obtain relative flow contribution and inflow performance under multi-rate testing conditions.
Using a structured approach, the inflow gas monitoring project included feasibility studies, well candidate selection, lessons learnt and developed best practices based on installations in six producing wells in the North Malay Basin (NMB).
A Novel Approach to Determine Reservoir Fluid Composition from Separator Test Data
Authors: Sequeira Daryl S. , Egbukole Okechukwu M. , Sahl Ahmed M. 
Published: September 2021

Abstract
High quality composition and PVT data can directly improve a wide range of upstream and downstreamengineering calculations. The quality of PVT Black oil experiments depends on awide variety of factors that includes type of PVT system, pressure-temperature conditions, stability and composition. The objective of this study is to emphasize the need to use material balance calculations obtainedfrom separator test data to back-calculate the reservoir composition andvalidate it against the original reservoir fluid composition.
The methodologies employed in this study involve the following steps;
Change Management: A Game Changer for Effective Digital Transformation
Authors: Udofia Emmanuel , Stanley Buduka 
Published: September 2021

Abstract
Change Management is a process of adopting appropriate guidelines on how to manage change and meet the set business objective. Change Management could be extended into the realm of providing leadership for a group of persons or organisation alongside the path of change and embed the needed framework in actualising the set business target. Conversely, Digital Transformation could be described as the deployment of technology in a business process to amplify business benefits realisation that include fast decision-making, efficient business processes and significant reduction in risk exposure through managing the operational risk foot print. Failures of many Digital Transformation initiatives around the world is traceable to poor framing or complete lack of change management process embedment in the implemented digital solution, this paper aims at proposing effective framework for embedding orchestrated change process.
Several research works show that worldwide there are high rate of project failures in most digital oilfield implementations. The reasons for such high failure rate in the solution of Digital Transformation is poor or lack of experience in change management in such projects resulting in poor framing of the change process that will ultimately assist in orchestrating the disruptions that accompanies the implemented Digital Transformation in different assets. This research based project will be reviewing how effective change management process was implemented in a digital solution by an Oil and gas operator in a field offshore in sub-Saharan Africa. Elements such as proper engagement of the workforce, defined business processes, clear business objectives and experience of the change agents in managing previous projects will be evaluated because these are components that has been identified as key reasons for failure of the change management process implementation in most digital initiatives. What companies need to do is to be strategic with the approach of implementation of digital oilfields transformation to ensure that the disruption brought about by the digital oilfields solutions are orchestrated through effective change management embedment.
The effective change management process, when applied, shows that orchestrated technology disruption process is embedded which will ultimately not just lead to benefit realisation of the solutions but will assure continuous business improvement process, overtime. The result of this study, has shown that effective change management processes are beneficial to the effective embedment of Digital Oilfields Transformation solutions. Outcome of this study could form a reference tool for similar robust digital oilfields transformation, elsewhere.
Incorporation Project as a Tool for Students' Integration into the Company's Business Processes
Authors: Kartavy Sergei , Eremina Irina , Sorokin Pavel , Zalevina Anna , Pisarev Mikhail , Korkishko Alexander , Nabokov Alexander 
Published: September 2021

Abstract
The name Incorporation refers to the major purpose of project, which it to early integrate university students into the business processes of a vertically integrated oil company. Developed jointly with partner universities, the project was created as a response to several challenges of the company related to providing cross-functional cooperation and training of highly qualified personnel for the company as well as soft early adaptation into company.
Incorporation involves the integration of Industrial and Civil Engineering students into the phase of field concept design, and the further development of a strategy of a construction project based on the oil company's real case. So far, the Incorporation project has been applied in the perimeter of the Capital Construction and Conceptual Engineering functions of a major oil company, but as an educational tool it can be extended to other functions.
As a result of two full annual streams of the project, the students of Master's degree programmes Conceptual Engineering for the Oil and Gas Industry at University of Tyumen (UTMN) and Industrial and Civil Engineering of Oil Production Facilities at Industrial University of Tyumen (IUT) developed key skills and got a system view for the value chain. This promotes the career guidance of students and their subsequent employment in accordance with their expectations and skills.
This article highlights Incorporation background, its goal and objectives, principles and actors, includes a full description of one project stream as well as results over two years of Incorporation implementation in a large oil company.
The purpose of the article is to demonstrate existing best practices in the training of hard skills and team as well as personal soft skills among students of specific Master's degree programmes who makes a talent pool of oil company.
Automatable High Sensitivity Tracer Detection: Toward Tracer Data Enriched Production Management of Hydrocarbon Reservoirs
Authors: Ow Hooisweng , Chang Sehoon , Thomas Gawain , Wang Wei , Mashat Afnan A. , Shateeb Hussein 
Published: September 2021

Abstract
The development of automatable high sensitivity analytical methods for tracer detection has been one of the most central challenges to realize ubiquitous full-field tracer deployment to study reservoirs with many cross-communicating injector and producer wells. Herein we report a tracer analysis approach, inspired by strategies commonly utilized in the biotechnology industry, that directly addresses key limitations in process throughput, detection sensitivity and automation potential of state-of-the-art technologies.
A two-dimensional high performance liquid chromatography (2D-HPLC) method was developed for the rapid fluorescence detection and simultaneous identification of a class of novel barcoded tracers in produced water down to ultra-trace concentration ranges (&lt;1ppb), matching the sensitivity of tracer technologies currently used in the oil industry. The sample preparation process throughput was significantly intensified by judicious adaptations of off-the-shelf biopharma automation solutions. The optical detection sensitivity was further improved by the time-resolved luminescence of the novel tracer materials that allows the negation of residual background signals from the produced water.
To showcase the potential, we applied this powerful separation and detection methodology to analyze field samples from two recent field validations of a novel class of optically detectable tracers, in which two novel tracers were injected along with a benchmarking conventional fluorobenzoic acid (FBA)-based tracer. The enhanced resolving power of the 2D chromatographic separation drastically suppressed the background signal, enabling the optical detection of a tracer species injected at 10x lower concentration. Further, we orthogonally confirmed the detection of this tracer species by the industry standard high-resolution accurate mass spectrometry (HRAM) technique, demonstrating comparable limits of detection. Tracer detection profile indicated that the transport behavior of the novel optical tracers through highly saline and retentive reservoir was similar to that of FBAs, validating the performance of this new class of tracers. Promising steps toward complete automation of the tracer separation and detection procedure have drastically reduced manual interventions and decreased the analysis cycle time, laying solid foundation to full-field deployment of tracers for better reservoir characterizations to inform decisions on production optimization.
This paper outlines the automatable tracer detection methodology that has been developed for robustness and simplicity, so that efficient utilization of the resultant high-resolution tracer data can be applied toward improving production strategy via intelligent and active rate adjustments.
Novel Application of Artificial Intelligence with Potential to Transform Well Planning Workflows on the Norwegian Continental Shelf
Authors: Vabø Jon Gustav , Delaney Evan Thomas , Savel Tom , Dolle Norbert 
Published: September 2021

Abstract
This paper describes the transformational application of Artificial Intelligence (AI) in Equinor's annual well planning and maturation process.
Well planning is a complex decision-making process, like many other processes in the industry. There are thousands of choices, conflicting business drivers, lots of uncertainty, and hidden bias. These complexities all add up, which makes good decision making very hard.
In this application, AI has been used for automated and unbiased evaluation of the full solution space, with the objective to optimize the selection of drilling campaigns while taking into account complex issues such as anti-collision with existing wells, drilling hazards and trade-offs between cost, value and risk.
Designing drillable well trajectories involves a sequence of decisions, which makes the process very suitable for AI algorithms. Different solver architectures, or algorithms, can be used to play this game. This is similar to how companies such as Google-owned DeepMind develop customized solvers for games such as Go and StarCraft.
The chosen method is a Tree Search algorithm with an evolutionary layer on top, providing a good balance in terms of performance (i.e., speed) vs. exploration capability (i.e., it looks "wide" in the option space).
The algorithm has been deployed in a full stack web-based application that allows users to follow an end-2-end workflow: from defining well trajectory design rules and constraints to running the AI engine and evaluating results to the optimization of multi-well drilling campaigns based on risk, value and cost objectives.
The full-size paper describes different Norwegian Continental Shelf (NCS) use cases of this AI assisted well trajectory planning.
Results to-date indicate significant CAPEX savings potential and step-change improvements in decision speed (months to days) compared to routine manual workflows.
There are very limited real transformative examples of Artificial Intelligence in multi- disciplinary workflows. This paper therefore gives a unique insight how a combination of data science, domain expertise and end user feedback can lead to powerful and transformative AI solutions – implemented at scale within an existing organization.
Natural Language Processing Applied to Reduction of False and Missed Alarms in Kick and Lost Circulation Detection
Authors: Yi Michael , Ashok Pradeepkumar , Ramos Dawson , Thetford Taylor , Bohlander Spencer , Moisan James , Behounek Michael 
Published: September 2021

Abstract
Kick and lost circulation events are large contributors to non-productive time. Therefore, early detection of these events is crucial. In the absence of good flow in and flow out sensors, pit volume trends offer the best possibility for influx/loss detection, but errors occur since external mud addition /removal to the pits is not monitored or sensed. The goal is to reduce false alarms caused by such mud additions and removal.
Data analyzed from over 100s of wells in North America show that mud addition and removal results in certain unique pit volume gain / loss trends, and these trends are quite different from a kick, a lost circulation or a wellbore breathing event trend. Additionally, driller's input text memos into the data aggregation system (EDR) and these memos often provide information with regards to pit operations. In this paper, we introduce a method that utilizes a Bayesian network to aggregate trends detected in time-series data with events identified by natural language processing (NLP) of driller memos critical to greatly improve the accuracy and robustness of kick and lost circulation detection.
The methodology was implemented in software that is currently running on rigs in North America. During the test phase, we applied it on several historical wells with lost circulation events and several historical wells with kick events. We were able to identify and quantify the losses even during connections and mud additions, where usually pit volume was increasing despite continual losses. Also, the real-time simultaneous analysis of driller memos provides context to pit volume trends and further reduce the false alarms. The algorithm is also able to take account of pit volume that was reduced due to drilling. Quantification of the losses offers more insight into what lost circulation material to use and the changes in the rate of loss while drilling. This approach was very robust in discovering kicks as well and differentiating it from mud addition and wellbore breathing events. These historical case studies will be detailed in this paper.
This is the first time that patterns in mud volume addition and removal detected from time-series data have been used along with driller memos using NLP to reduce false alerts in kick and lost circulation detection. This approach is particularly useful in identifying kick and lost circulation events from pit volume data, especially when good flow in and flow out sensors are not available. The paper provides guidance on how real-time sensor data can be combined with textual data to improve the outputs from an advisory system.