bluuebunny/crossref_metadata_2025_split huggingface dataset:
Field X's Journey to the Best-In-Class Performance, Using the Gap-To-Potential Approach
Authors: Shukaili Ghosin AL , Kindi Said Al , Riyami Said Al , Hatmi Fahad Al , Ajmi Ajmed Al , RIYAMI Yaqoob Al , Lawati Mehdi Al , Ghadani Adnan Al , Ismail Ahmed Al , Almatroushi Saif 
Published: November 2024

Abstract
Field X is the largest oil field in Petroleum Development Oman (PDO), with the most wells and the highest production. It is also a very mature field, with many old wells and aging facilities. This means that it is important to manage the field carefully to maintain production and prevent decline. In 2020, Field X's performance was below industry standards. The subsurface unscheduled deferment was on the rise (reaching 3.7% of total field potential in 2020), the artificial lift failure index was high (28%), the number of closed-in wells (CIW) with potential was high (9.1%), and the oil gain from optimization activities was low (3.1%). To improve performance, the team embarked on a journey towards WRFM Excellence. They used a Gap to Potential (GtP) benchmarking approach to identify and address performance gaps.
The team successfully executed their strategy, and Field X's WRM performance is now best-in-class. This was achieved through effective collaboration between different departments, agile work processes, the use of technology, automation, and visual management.
Between 2020 and 2023, there has been a dramatic improvement in Field X's performance. For example, the subsurface unscheduled deferment rate has decreased from 3.7% to 2.1%, and some fields have achieved ZERO unscheduled subsurface deferment. The artificial lift failure index has also dropped from 28% to 18%, and the CIW stock has dropped from 9.1% to 4.6%. The oil gain from Optimization has even doubled, from 3.1% to 7.2%. In addition to these performance improvements, the successful deployment of the GPT approach also had a positive impact on Health, Safety, and Environment (HSE), as all projects were executed safely with zero lost time injuries. Furthermore, the conversion of 40 wells from beam pump to Long Stork Unites LSU resulted in a 40% reduction in energy consumption and CO2 emissions.
Overall, the results of the GPT approach in Field X are very impressive. The team was able to achieve significant improvements in performance, HSE, and sustainability. This is a great example of how the GPT approach can be used to improve the performance of oil and gas fields. This paper reports on the successful implementation of the Field X Gap-to-Potential (GPT) approach, resulting in best-in-class performance.
A Novel Technology for Low-Carbon Hydrogen from H2S: A Large-Scale Techno-Economic and Environmental Assessment
Authors: Ali Sawsan. M. , Al Khatib Ismail. I. , Vega Lourdes. F. 
Published: November 2024

Abstract
H2S, a waste gas in oil & gas industry is usually incinerated in the Claus process. H2S-methane reforming (H2SMR) is a new technology developed at KU-RICH for producing low-cost and low-carbon hydrogen, key for the hydrogen economy. This work provides a comparative techno-economic and environmental assessment for alternative hydrogen-production via H2S methane reforming where H2S substitutes water in the conventional Steam methane reforming process (SMR). A large-scale H2SMR process is developed and benchmarked against SMR with CO2 capture (SMR+CC) in addition to methane thermal decomposition (CH4Pyrol). The study reveals the comparable energy intensity of H2SMR and SMR+CC at 148-149 MJ.kgH2-1 while CH4Pyrol has the least energy intensity of 75 MJ.kgH2-1. The added-value of process by-products of H2SMR and CH4Pyrol improved their levelized cost of hydrogen (LCOH) to $-1.00 and $1.93 per Kg, respectively compared to SMR+CC with $4.13 per kg and $2.41 per kg excluding and including CO2 selling credits. The carbon footprint of the three pathways is demonstrated via a gate-to-gate lifecycle assessment obtained in the order of H2SMR &lt; CH4Pyrol&lt; SMR+CC.
Artificial Lift Optimization with Clamp-On Multiphase Flowmeter
Authors: Black M. , Heinks C. , Cramer R. 
Published: November 2024

Abstract
This paper examines how clamp-on multiphase flowmeters can be used to optimize the performance of oilfield assets, such as artificial lift systems on unconventional wells. A clamp-on Electromagnetic Acoustic Transducer (EMAT) multiphase metering system has been developed that can be rapidly installed on all, or some of the production flow lines of new wells or retrofitted to existing wells with zero intervention. The EMAT measurement approach is clamp-on and non-radioactive. Examples of EMAT real time field measurements shall be presented and how the resulting data can be used to improve asset performance/integrity.
The workflow used to configure the meter prior to installation to the line shall be described. This includes empirical and physics-based flow analysis of reported well conditions based on pipe geometry, production data and PVT information plus in this case analysis of the dynamics of artificial lift systems for given wells. EMAT flowmeters were brought to multiple well sites and installed on producing flowlines downstream of the well heads where measurements were taken, and the configuration of the artificial lift system was noted. Results obtained were analyzed to assess the performance of the artificial lift systems.
The EMAT flowmeter was installed on several wells with an installation time less than one hour and with zero intervention. In preparation for each well, simulations were performed using the Taitel and Dukler model [1,2] to predict the flow regime. Traditionally such simulations use average flow values as measured by the test separator, but in this case the real time, multiphase dynamics of the artificial lift system as measured by the EMAT meter can be taken into consideration, because in many cases the flow is fluctuating around this average value. EMAT real-time high frequency multiphase flow measurements were used to provide a more realistic simulation capability which cannot be delivered by conventional test separators. The EMAT flowmeter embellished simulations were used to deliver improved data for each well, thus providing a detailed understanding of the flow regime within the flow line. These data were then used to better understand the dynamics, flow regime and performance of the artificial lift system e.g. rapid identification of damaging conditions that can reduce the productivity and lifetime of downhole pumps.
The EMAT measurement technique is a novel approach for multiphase clamp-on well monitoring. Using multiphase flow data, including high frequency measurement and assessment of flow regimes within the pipe, to assess artificial lift performance is unique and qualitatively different to typical applications such as well testing. Improving the performance of artificial lift can lead to larger scale objectives such as optimization across the reservoir.
Advanced Well Test Advisory System and Virtual Flow Metering to Improve Production Allocation and Well Surveillance. A Success Case in a Major Middle East Oil Company
Authors: Davila Rayner , Al Braiki Warda Awadh , Molina Adriana , Alyaqoubi Afra , Aladsani Amna Salem , Bahumaish Fatima , Ofodile Azubuike , Halvorson Steven , Bakhti Sara , Braunschweig Lukas , Lu Dennis , Khare Kautuk , Aydin Murat 
Published: November 2024

Abstract
This paper demonstrates a successful example of a technology pilot that solved technical challenges related to well testing and production allocation. Two tools, called i-WellTest and WellAware, were developed in nearly 3 month that supports well testing process from start to finish, including prioritization by exception based on real time well head parameters, smart guidance, scheduling, live monitoring, automated validation, as well as provide six alternates well rate estimation methods including one AI.
Accurate well allocation ensures efficient production performance. Engineers struggle to accurately estimate daily well rates, well statuses, and effectively identify underperforming wells due to limited access to well sensor data and absence of integrated production systems. This results in undetected production issues, and high uncertainty on well allocation factors, especially for gas lifted wells.
Working collaboratively with Palantir, 10 oil producers were selected, equipped with sensors able to get well head parameters, choke size, gas lift rates, valve status and MPFM readings. Pilot was conducted in two phases: first month discovering the value, and second month validating it.
i-WellTest is a real time application designed to assist engineers prior, during and after a test is conducted. It includes prioritization, scheduling, online validation, and report automation to optimize the entire well test process. Wells are to be tested by exception when their performance changes significantly, and while being on test, i-WellTest provides advice to engineers on the issues of optimal stabilization time, test duration, quality of the results, and the final validation. All of these issues are tackled by using a combination of online, data driven models and pattern recognition being fed by real time data from well and testing facilities.
i-WellTest makes the Well Testing process more transparent for the teams involved by allowing engineers to operate from a common view of the world which provides a granular understanding of well tests. This has led to the opportunity of reducing testing durations which, if taken, could translate into a significant reduction of Field deferred production.
Well test advisory system and virtual flow metering provides an unprecedented solution for long lasting technical challenges and limitations, in roughly three months it was accomplished what normally would have taken a year or more. Our engineers can now see things, do things, and work collaboratively in ways they could not have before. It demonstrated success case on how real technical issues can be addressed quickly by embracing cutting edge technologies.
The Algorithm for Monitoring and Managing Wells with Sanding Issues
Authors: Kovacevic Strahinja , Mihailovic Slobodan 
Published: November 2024

Abstract
The goal of this study is to create an algorithm for identifying problematic wells with sanding issues in mature oil fields, producing with Cased Hole Gravel Pack as the predominant sand control technology. In most cases, problematic wells selection is actually the choice of underperforming wells. However, this simplified interpretation (clarification) may result in the selection of wrong candidates and the implementation of inadequate solutions and technologies aimed at solving certain problems that cause production performance to decrease.
The first step in this process was to identify all parameters that are related to well production from unconsolidated reservoirs. Then this data was matched with the implemented sand control technology and its design. With deep-dive analysis of workover and production history in this field and depending on specific issues that had been occurring regularly, we were able to develop a series of questions and answers that led to a specific solution. In this way, an algorithm for identifying problematic wells and choosing the right solutions was created.
This algorithm offers a new, systematic and detailed approach to managing the oil wells with sanding issues, giving the guidelines for establishing the problematic wells and measures for restoring the production level. In this way, it provides a cost-effective analysis tool because it reduces expenditures for poor decisions when dealing with sanding problems. Similar algorithms could be created for wells with other issues, such as gas interference, poor inflow, paraffin depositions, etc.
An Integrated Analytical Technique to Screen Depleted Reservoirs for Underground Gas Storage Suitability
Authors: Telang V. N. , Mohamed Y. , Eldin S. S. , Chughtai M. , Singh H. , Pandya S. , Mascagnini C. , Perumalla S. 
Published: November 2024

Abstract
Underground gas storage (UGS) technique is gaining impetus and is widely implemented due to the global gas demand and consequent variation of gas prices. Due to the upfront investment involved in UGS projects, thorough screening of potential candidate reservoirs followed by economic feasibility analysis is essential to ensure the functionality of the project.
A range of technical factors like reservoir containment, gas recovery, pressure regimes throughout the operation, well integrity, available surface equipment, presence of contaminants in the fluid and project safety are considered as a part of the reservoir screening and UGS design workflow. Cushion gas requirement, working gas capacity, and maximum gas injection/ withdrawal requirements are the key operating elements that drive the feasibility and design of a UGS project. Finally, risk evaluation, economic feasibility and policy factors are reviewed to assess the feasibility of the candidate reservoir for a UGS project.
The study encompassed evaluation of three depleted fields for UGS candidacy. The two smaller fields offer very limited storage volumes and were deemed as unsuitable due to target extraction and storage rates. The bigger structure was delineated as a potential candidate. Geological investigation affirmed the caprock seal integrity. Formation pressure data confirmed hydraulic connectivity of the reservoir that was continuous to an adjacent structure. However, this connectivity was constrained by a gas-water contact (GWC) that acted as the bottom boundary for the containment. After calibrating the model with a fit-for-purpose objective, the reservoir modelling identified opportunities for maximizing working gas capacity through sensitivity analysis. Well engineering and completion assessments qualified existing wells for conversion to injectors, identify potential workover requirements and propose upgrades to existing equipment. Overall, the reservoir was qualified as good candidate for UGS requiring an additional investment circa $200Mn towards UGS specific surface facility with 30% uncertainty.
Based on the meticulous review and integration of outcomes from multiple disciplines, a quick analytical technique based on material balance and production performance prediction was developed. This workflow was carefully implemented to assess the UGS candidacy of a similar reservoir in a nearby field. Further development of the workflow has the potential to serve as quick-look tool and precursor to the detail oriented integrated approach described earlier.
Successful Trial of Innovative Sand Fallback Eliminator System for ESP Wells in KOC Fields
Authors: Al-Abdullah Hashem , Saud Ammar , Al-Rasheedi Khaled , Jalan Shiv , Tirkey Naween , Al-Rughaib Sara , ElKhalil Samer 
Published: November 2024

Abstract
Electrical Submersible Pumps are widely used in Kuwait Oil Company (KOC) fields in order to enhance or sustain production from matured oil fields. These high-power electro-mechanical systems are susceptible to failure due to various reasons, leading to high work-over rig intervention costs and time, in addition to substantial production deferment.
The objective of this pilot trial was to apprise applicability and feasibility of an economic innovative solution in order to address sand and debris fallback during ESP trips and shutdowns periods.
The available conventional systems within KOC to tackle the sand fallback challenge in ESP wells are not efficient or durable. It fails in a short time, leading to a significant impact on the well's deliverability and operating costs.
In 2021, KOC started applying a unique solution on wells where the ESP run life was short due to solid and sand fallback accumulating on top of the pump during ESP trips and shutdown periods. This patent-protected technology diverts falling back sand, solids, and debris into the outer chamber of the tool and quarantines them away from the pump. Upon ESP restart, internal dynamic flow ports agitate sand, and solids caught in the tool's chamber carries them to surface along with the produced fluids.
This pilot trial has gone through different stages including challenge identification, technology survey, candidate well selection process, business cases build-up, success criteria, execution and evaluation phases.
Well's performance were evaluated rigorously before and after this unique system installation for a duration of six (6) months. Several KPIs were set to conclude and judge the technology such as: ESP sensor data, ESP run life and well productivity, it was concluded that this innovative technology was able to significantly improve well's productivity and achieve prolonged ESP run life compared to the currently adopted conventional techniques.
This paper highlights in further details the operational challenges and failures due to sand fallback, technical features of this field proven technology, sharing the success case studies and shed light on the captured lessons learned for continuous improvement & optimization.
The novelty of this technology is the ability to provide a cost-effective durable solution for sand fallback issue in ESP wells to extend ESP run life, achieve production improvement and avoid costly workovers and production deferment.
Development Design of Midland Basin Edge Using Measurements and Modeling
Authors: Malpani Raj , Lyons Shelby L. , Kumar D. Satish , Bhatnagar Ankit , Bhatt Divyanshu , Tahir Hussain , Heij Gerhard , Every Sean , Lopez Cucha , Felts Libby , Meier Holger A. 
Published: November 2024

Abstract
The Midland basin is one of the most actively developed basins in the world. The primary unconventional reservoirs, Wolfcamp and Spraberry, are targeted basin-wide by various operators. While many of the development decisions across the broader Midland basin are well studied and published, including target benches/sub-benches, well spacing, completion intensity, and frac order, there is often limited applicability of prior data and learnings to structurally isolated mini-basins within Midland basin.
To better understand fracture growth, vertical communication, and development choices specific to the mini-basin, a data acquisition program was designed and executed. The data acquisition program consisted of a vertical well with open hole logging suite, geochemistry sampling, and external pressure gauges. In addition, six horizontal wells were monitored during the stimulation and production phases.
Interpretation of the acquired data, coupled with integrated fracture and reservoir models, enabled rigorous testing/validation of development choices. Fracture sequence and completion intensity has been observed to refine well spacing and target benches. This paper covers the integrated workflow that coupled interpretation of data acquired through a unique data acquisition program, modeling, and sensitivity analysis to inform future development and targeted appraisal choices in the mini-basin.
Integrated Workflow with Mechanical and Chemical Solutions for Offshore UAE Coiled Tubing Strontium Sulfate Scale Removal
Authors: Khalil Ur Rehman. H. , Arali V. B. , Franco Delgado , E. ElAttar A. , Ryan A. , Mahmoud W. , Alam S. S. , Abolmaali M. 
Published: November 2024

Abstract
Sulfate scale formation, caused by the mixing of sulfate-rich seawater with barium or strontium-rich formation water, hinders oil and gas production by reducing flow rates and damaging equipment. Removing sulfate scales from wells is challenging because of their hardness, chemical resistance, strong adherence, and the operational and environmental complexities involved. Additionally, handling them poses safety concerns as they are classified as technologically enhanced naturally occurring radioactive materials (TENORM), requiring strict safety protocols.
The primary objective of this project was to remove challenging hard scale for an operator in the UAE offshore oilfields, which impaired production and accessibility for well intervention using coiled tubing (CT) milling solutions and innovative chemistry. The operator faced serious issues with strontium sulfate (SrSO4) accumulation on offshore locations that obstructed production flow, necessitating frequent and costly hydraulic workover unit (HWU) operations for full completion replacement.
A scale removal workflow was developed using a 2.75-in. and 2.50-in. outside diameter (OD) diamond mill bit in conjunction with chelating sulfate solvents to address the hard SrSO4 scale. Diamond mill bits, chosen for their superior cutting efficiency and wear resistance, were used alongside a chelating agent (CA) identified through laboratory tests as the most effective dissolver, achieving 100% scale dissolution within a period of 24 hours. Periodic soaking with the CA softened the scale, enhancing the rate of penetration (ROP) from 2 to 5 ft/hr to an average of 20 ft/hr. This approach enabled the removal of SrSO4 scale in two wells, successfully restoring the original well production by and establishing a new precedent for offshore rigless interventions.
Leveraging Reservoir Knowledge, Multi-Scenario Modelling and Artificial Intelligence to Robustly Screen Development Options on a Click of a Button
Authors: Munira Hadhrami , Robert Bos , Vedant Kumar , Louis Dcosta , Abdulla Hamdi 
Published: November 2024

Abstract
During the past decade, Petroleum Development Oman's Hydrocarbon Maturation Centre (HMC) has established thematic catalogues with reservoir knowledge for various formations in PDO's acreage. The objective of this multidisciplinary collection of data, experience and insights is to reduce FDP cycle times by providing users web-based access to standardized datasets, workflows and past development decisions and thereby leveraging the use of analogues for development decision making. However, despite the vast amount of analogue information specific development decisions such as optimal pattern type, well spacing, water throughput, etc. and corresponding recovery factors and production profiles are still evaluated using conventional forecasting tools, which are seemingly time and resources consuming.
In this project, PDO has developed an innovative web-based tool that leverages the extensive analogue knowledge, multi-scenario modelling, and Artificial Intelligence (AI) to eliminate or significantly reduce the requirement for such reservoir simulation studies. For several reservoirs formations, 10,000's of sector simulation models were built, covering all possible combination of static and dynamic parameters with the uncertainty ranges quantified in the thematic catalogues and representing the most common development concepts. The entire dataset is then used to train AI models and build the model library.
The generated sector model library is searchable and can be used to identify reservoir analogues. The AI webtool then can predict recovery factors, forecast profile ranges etc. for any analogue or new sector model for the available development concepts at a click of a button. This allows a fast & robust evaluation of subsurface development options with clarity on trade off's, eliminates repetitive modelling & simulation requirements, and significantly accelerates simulation-based forecasting by 50% or more.
Unlike most traditional forecast prediction tools, available in the company, the FDIC-AI dashboard is based on extensive multi-scenario modelling and simulation results and use artificial intelligence to create predictions for any reservoir models with parameter combination within the defined ranges. This means that the tool can 1) generate valuable insights on production behaviour based on geological characteristics and development concept, II) be used for predictive analysis and benchmarking of reservoir expected performance, III) improve the efficiency in making early decisions on development concept decisions by quantifying trade-offs, VI) support the aspiration of the company towards leveraging analogue-based developments and agility in delivering projects.