bluuebunny/crossref_metadata_2025_split huggingface dataset:
Conquer Liquid Loading in Raageshwari Gas Field by Automated Intermittent Production and Deliquification
Authors: Johri Nitin , Kadam Sanket , Veeken Kees , Prakash Aditya , Suvarna Hrithik , Singh Prakhar , Daukia Shashank , Kadirus Sandeep , Goswami Anindya , Aakash Suyash 
Published: October 2023

Abstract
The Raageshwari gas field is a tight, highly laminated retrograde gas condensate reservoir. The field is developed by multistage fracturing of wells with 3-1/2" and 4-1/2" monobore completions. Many wells have started liquid loading and are producing intermittent which reduces production capacity and restricts ultimate recovery. This paper presents efforts to date, first to manage intermittent production and second to restore stable production and increase ultimate recovery by means of deliquification.
After the onset of liquid loading, intermittent production is optimized by automating the production and shut-in periods. This allows time to evaluate, select and implement deliquification measures to delay well abandonment and maximize ultimate recovery. This paper describes the results of three deliquification techniques i.e. (1) Velocity String (VS), (2) Foam-Assisted Lift (FAL), and (3) Surface Gas Ejector.
Inflow performance is key to forecasting the incremental production associated with deliquification. With limited bottomhole data, surface production data was used to estimate both reservoir pressure and inflow resistance.
SmartVessel-v2: A Faster, Better, Stronger, Safety Monitoring Solution for Marine Vessels
Authors: Egorov D. , Sharan S. , Tahiri M. , Tamaazousti Y. , Amri M. 
Published: October 2023

Abstract
At ADIPEC'2022, SmartVessel, a vision-based HSE monitoring system, showed remarkable results in addressing HSE challenges in Marine Vessels. Despite its innovative features, SmartVessel was limited in its analysis of operational situation on working site as it relies solely on images, lacking temporal context. This deficiency leads to numerous false alarms and unnecessary operations interruptions. To address this issue, the new version of AI solution called SmartVessel-v2 was proposed. Despite the large number of advances, the main one can be called features tracking capabilities and temporal modeling. The brand-new version promises higher accuracy and efficiency, less false alarms and at higher running speed, increasing the safety of workers on-site.
The goal of this paper is to present the recent advances of previously presented AI based HSE surveillance system. The paper covers new safety related business cases introduced in the solution and corresponding novel algorithms to process and analyze them. It also highlights overall advances of AI pipeline helped to achieve higher level of accuracy and outstanding reduction in number of false alarms.
The last but not least, experience of solution large scale deployment for a whole fleet is described to share the knowledge about challenges, lessons learned and best practices how to handle this process in the optimal way. It can be extremely useful for all steps of design, development and deployment for any AI-based CCTV because it helps organize the process in correct way and avoid potential issues related to hardware and infrastructure, environmental, business and operational issues.
Re-Development of Tight Fractured Carbonates Through Extended Laterals and Hydraulic Fracturing
Authors: Buono A. , Taylor C. , Dordan A. , Evans B. , Staus G. , Zhu C. , MacQuaker J. 
Published: October 2023

Abstract
In this paper we compare development scenarios in a fractured carbonate play between historic vertical/short horizontal development and modern hydraulically fractured extended lateral development. The hydrocarbon production is analyzed and compared from fracture versus matrix play perspectives in this tight carbonate play. Here we are explicitly investigating the utility of applying unconventional technology to traditionally low/variably producing carbonate reservoirs as a means of increasing EUR and decreasing development scale variability. To meet this objective, we analyzed representative historical production data from a naturally fractured, fine-grained calcareous reservoir and compared it to production from the same unit where unconventional technology has been used to stimulate additional production from the matrix components. Due to its long production history and recent redevelopment efforts by industry, the Austin Chalk was chosen as a natural laboratory to test how recent artificial stimulation techniques lead to additional production from a wider range of pore systems.
We utilized petrophysical and microscopy data to compare rock attributes between the most common historic landing zone and the artificially stimulated zone, and determined the origin of the fluids produced from the stimulated zones. Additionally, we used production data from offset wells where different development strategies had been used as a method of comparing real world results as they relate to the study. The resulting data were then assessed in terms of matrix vs fracture delivery and zonal contributions to produced oils. We found that drainages of hydrocarbons produced from Austin Chalk landed wells ranged from Austin Chalk C Zone to the Eagle Ford/K64SB Zone; whereas hydrocarbons produced from Eagle Ford landed wells predominately drained the Eagle Ford/K64S Zone. These data reveal that utilizing unconventional technology to redevelop tight carbonate fields can lead to significant uplift in both well productivity and field life. This approach has the potential to be deployed in tight carbonate/fractured carbonate plays globally.
A New Inflow Performance Relationship for Shale Gas Reservoirs Using Well Logs and Geochemistry Data
Authors: Oshaish Ali , Alnuaim Sami , Hassan Amjed , Mahmoud Mohamed 
Published: October 2023

Abstract
Exploiting the unconventional oil and gas resources has been sparked recently. Evaluating the well productivity in shale formations based on bare test rates is challenging and requires extensive work of simulation and extended periods of well testing. This work introduces a new, simple, and efficient IPR model for estimating the production performance from unconventional shale reservoirs at early stages of drilling and production. The implementation of this IPR model depends mainly on the integration between well logs and geochemical pyrolysis data to estimate the hydrocarbon potential in the reservoir. The proposed IPR model was applied using real data from shale gas reservoirs.
In this work, the well logs were initially analyzed to stratify the pay zone and to obtain the gas saturation. Then, an analytical correlation was derived to convert the organic richness indicator of the free and adsorbed gas (S1) to an incremental porosity and gas saturation values. After that, the final porosity and saturation profiles, along with the other petrophysical data were incorporated into a fractured reservoir simulation model using a commercial reservoir simulator (CMG). Then, the production outcomes of the simulation model were collected to be used in generating the IPR model as a function of the petrophysical and the pyrolysis data.
The results showed an excellent correlation between well performance, logging, and the pyrolysis data. The developed IPR formula was found in the form of famous Fitkovich’s back pressure model which fitted the simulator generated production data at different reservoir pressures with R2 value of 0.99 for different reservoir pressures. Moreover, the exponent (n) in Fetkovich’s IPR model which ranges from 0.5 to 1 in conventional reservoirs, was found to be greater than 1 in unconventional shale gas reservoirs. This finding was examined in a case study using real production data. On the other hand, the log C value, which is involved in the y-intercept of the logarithmic transformation of Fetkovich IPR, was seen to be dependent on reservoir’s characteristics and geochemical properties such as bed thickness, gas saturation, porosity, and organic production index (PI).
Overall, the study aims to develop a simple IPR model to estimate well productivity in shale gas reservoirs based on the available logging and pyrolysis data during the early stages of drilling and completion. Moreover, the proposed model can be integrated with Logging While Drilling (LWD) operation for real-time estimation of well productivity. For the first time, the geochemical properties are integrated with the logging data to provide an IPR model that considers the free and adsorbed gas in the shale formations.
Petrophysical Reservoir Property Prediction from Seismic Data. Bridging the Geophysical Properties to Geological Information. Case Study from Marib Basin Yemen, Alif Formation
Authors: Al-Maktari Amin , Al Shadadi Aref , Ali Al-Rawqi Mohammed , Aly Omar , Ibrahim Aya , Nafie Tarek 
Published: October 2023

Abstract

Objectives
The objective of this study is to understand the reservoir properties distribution of the Alif formation from seismic data and to Enhance the seismic interpretation model for well planning Support. This is to minimize the drilling risk associated with rapid spatial heterogeneity and compartmentalization of the current reservoir rocks. Seismic inversion and Rock physics are powerful tools that delivers information about intra-wells rocks elastic attributes and reservoir properties such as porosity, saturation, and rock lithology classification.
The paper provides detailed and comprehensive technical details of the Surface Seismic and Rockphysics Inversion study that has been carried out on the current project to characterize the reservoir properties of the Alif formation from the seismic

Challenges
There are several challenges related to the characterization of the current reservoir rocks. The reservoir rocks are affected by a series of complex fault systems. In addition, the rocks are characterized by a high horizontal and vertical heterogeneity of their reservoir properties distribution (Porosity, Saturation, and Rock Facies), which is tough to resolve using seismic imaging techniques alone.
It was crucial to go beyond seismic imaging techniques to better characterize the reservoir rocks in terms of reservoir properties such as Effective Porosity, Water Saturation, and Rock, Classification.
Geophysical logs including sonic and density logs, measure rock properties near the borehole. The reliability of these logs is affected by borehole diameter and shape, as well as drilling fluid invasion. Acoustic well logs need to be conditioned before being used in geophysical analysis as any error propagate through the subsequent processes.
Surface seismic data quality is impacted by residual noise, multiples contamination, and improper amplitude balancing. To optimize processing for inversion studies. Processes include curvelet domain noise attenuation, high-resolution Radon anti-multiple, and extended interbed multiple Prediction. Offset dependent amplitude and spectral balancing are applied to maintain seismic amplitude fidelity.
Multi-Scale Reservoir Characterization of a Diagenetically Complex Tight-Gas Reservoir; The Miqrat Formation, Oman
Authors: Al Hajri Salim N. , Merletti German , Armitage Peter , Al Rashdi Khalil , Gray Ewan , Al Saadi Sawsan 
Published: October 2023

Abstract
The Miqrat Formation is a Cambrian tight-gas (low permeability) reservoir in the Khazzan and Ghazeer fields (Block 61), which together with the Barik Formation comprise the most prolific gas and condensate reservoirs in northern Oman. The reservoir quality of these sandstones is controlled by the depositional environment, ensuing diagenesis, timing of liquid hydrocarbon charge and subsequent replacement by gas and condensate. The development of the Miqrat is challenged by its geological complexity and this study demonstrates an integrated multi scale workflow to reduce risk and uncertainty in developing these reservoirs.
The Miqrat was deposited in alluvial plain and lacustrine sedimentary environments. The environment and provenance formed a mineralogically and texturally variable sediment at deposition, which has been diagenetically modified and degraded during subsequent burial history (maximum burial depth exceeding 5km). Understanding the heterogeneity of these sandstones at a range of scales is crucial in understanding the key risk of reservoir deliverability. To address this, we have accomplished a comprehensive core analysis programme including Nuclear Magnetic Resonance (NMR), and thin section petrology to identify the complex diagenetic and sedimentological controls on reservoir quality and their relationship to bound and moveable fluids. These plug scale measurements are upscaled to log scale where emphasis is placed on reservoir permeability. Log-derived models include porosity- and rock type-based trends. Water saturation models include the verification of potential deep conductive mud-filtrate invasion using resistivity modeling workflows.
Core-derived porosity and permeability plots show scattered, disguised trends demonstrating multiple competing controls on reservoir quality. Integration of post-hydraulic fracture clean up and flow tests provide additional evidence for larger scale reservoir complexity. Wells having similar log-derived gas absolute permeability thickness (KabsH) exhibit a wide range of initial reservoir performance. Core-calibrated, log-derived models are utilized to generate sand-thickness, pore thickness, absolute and gas effective permeability maps, to reveal the extent of the container, its space for fluids, and its lateral deliverability. Petrophysical maps are integrated to the understanding of hydraulic fracture propagation and well test results to further identify potential inter-well heterogeneity.
This paper demonstrates an integrated multi-scale workflow that effectively reduces uncertainty in the prediction of initial gas production to de-risk development in a complex reservoir.
Rig Sensor Data for AI-ML Technology-Based Solutions: Research, Development, and Innovations
Authors: Gamal Hany , Elkatatny Salaheldin , Al Gharbi Salem 
Published: October 2023

Abstract
The oil and gas industry is currently witnessing a notable shift towards automation and digitalization, driven by cutting-edge technologies like artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and big data analytics. These advanced solutions are being implemented to enhance operational efficiency, improve profitability, and enable data-driven decision-making. Among the various segments of the petroleum industry, drilling operations for oil and gas wells hold immense significance due to the high sharing of the total well cost. Therefore, the adoption of technology-driven solutions is crucial to ensure safe operations and cost reduction. This paper presents the successful applications overview of machine learning in the drilling operations domain and addresses the existing challenges and future opportunities in this field.
Surface drilling sensors record real-time drilling parameters such as weight on bit, hook load, drill string rotation, drilling torque, pumping rate and pressure, and rate of penetration. These drilling data parameters provide valuable information about the characteristics of the drilled rock, requiring appropriate preprocessing techniques for data quality improvement. Data collection, preprocessing, analysis, and the development of machine learning models for prediction and classification in drilling operations are significant areas of research. Numerous researchers have utilized drilling data in machine learning applications to predict and optimize drilling rate, drill string vibrations, rock characteristics, and other important variables. These models contribute to optimizing drilling parameters, enhancing operational performance, and reducing costs. The paper technically discusses the achievements in ML research and industrial applications within the drilling domain that cover various ML techniques, different data sources, diverse training data for model features, and the target outputs from the developed models.
The research findings highlight the exceptional performance of ML applications, technically and economically, by showcasing successful case studies from the industry. Through the analysis of observations, valuable recommendations and potential future opportunities have been identified. These findings open up promising avenues for improvement and development in various areas. ML applications in drilling data have significantly contributed to the industry and academia by enabling real-time monitoring, advisory systems, automation, digitalization, and accurate prediction and classification through developed ML models.
Thermoplastic Lined Tubing: A Cost-Effective and Uptime-Enhancing Solution to Prolong Well Run Life
Authors: Alisaee M. K. , Al Hinai M. I. , Al-Mandhari S. , Al Riyami S. Y. , Al Saadi F. , Alhinai G. , Al Busaidi I. K. , Al Harthy A. H. , Al Masfry R. , Al Suleimani A. , Al Riyami H. 
Published: October 2023

Abstract
Production deferment and its associated costs are one of the key challenges in Well Reservoir Formation Management (WRFM) environment especially as wells are aging and frequently failing prior to their expected well life span. This could happen due to various reasons and one of them is the tubing erosion/corrosion in artificially lifted wells such as PCP and ESP. Therefore, the idea of installing thermoplastic lined tubing came up as an attempt to prolong the completion run life and thus reduce oil deferment along with CAPEX and OPEX.
Fields in South of Oman operate at harsh reservoir conditions. Wells are producing relatively heavy oil at high BSW and high sand content. In 2020, hoist intervened 31 times in two fields (A and B) with a total of 70 active PCP wells only. 74% of failures were attributed to hole in tubing and 60% of these had less than one year run life. These alarming statistics necessitated out-of-the-box thinking. Thermoplastic lined tubing came into a picture as a mean of reducing failures by minimizing the friction between tubing and pump rods. This new method was first piloted in PDO in four wells in field A.
Despite being installed for over two years, none of the wells in pilot have failed till to date. Completion run life has increased by double and nearly triple in some cases and wells are still continuously operating successfully. This is a great achievement when it comes to deferment and cost reduction. In field A & B, each hoist intervention cost $100-150k, and deferment might last for 20-40 days before well restoration take place.
Preliminary results showed a saving of three interventions per well within two years and an increase of well uptime. The successful results extended the current plan to full deployment that will include other artificial lift well types. Furthermore, more than 30 thermoplastics lined tubing installations are currently expected per year in different fields for different clusters in PDO.
Thermoplastic lined tubing has not only proven to increase completion run life but also improve workovers cost and has element of energy saving due to reducing friction loss between pump rods and the internal of the tubing. This means less pump torque and less power consumption to lift the fluid to surface with an estimated power saving of 7-10%.
Lessons Learnt on How to Do a Successful Pressure While Drilling Tests Despite Challenging Environment in Middle East
Authors: Al Riyami N. H. , Espinoza I. Baca 
Published: October 2023

Abstract
The pressure testing while drilling (PTWD) is one of the fastest ways how to confirm the reservoir pressure and mobility when planning the advance completions. An accurate evaluation of the pore pressure is helping to avoid the formation damage caused by overbalance and to reduce the drilling risks, associated with lost circulation, drill pipe stuck, as well as hole un-stability.
Some factors affecting the quality of pretests while drilling includes highly deviated and extended-reach horizontal drains; mud systems, such as heavy mud, oil-based mud (OBM), and high solid contents. Other challenges might be associated with unknown washouts area; well losses as well as the urgency of doing the pretests directly after drilling. The mixed lithology with various shale, anhydrite, carbonate, or sandstone content might reduce the permeability and affect the PTWD program’s success. To improve the quality of the PTWD several factors need to be assessed, such as potential loss of the seal due to the washout or fractures; sufficient timing for the mud cake; tightness of the zone above or below the probe; corrective sequence of the test parameters.
There are several scenarios were evaluated to enhance the PTWD performance. First, the mud invasion across the highly permeable formation was expected to form a fast mud cake. The results show that for the cases with mobility of more than 20mD/cP the sufficient repeatable test could be acquired as soon as 2hrs with pumps-off acquisition mode. Secondly, the cases across the tight formation with &lt;10% p.u. were evaluated. Typically, the filtrate invasion in low permeability is very slow and if the PWD acquisition was too early, the pressure tests have no repeatability. In the third scenario, the tests were acquired 4 times across the same depth point with a very low porosity zone and a few hours between each pretest. It was visible how the mud was formed and how the pressure was reduced till the actual formation pressure only after 15 hrs from drilling. To avoid misleading pressure tests, it is recommended to plot the expected fluid gradient on top of a single valid point that has more than ~10 mD/cP mobility. For the cases with lower mobility, it is recommended to obtain three low-volume pretests with short build-up times and to repeat pretests in the nearby footage. The pump-off function is recommended for all pretests. For the cases where it is critical to have a real-time curve, it is recommended to repeat the test with pumps on only after completing the pumps off test. The OBM find to be helpful in wellbore stability and helps to improve the PTWD quality.
The result of this study shows the steps on how to plan the successful PTWD acquisition despite the formation and wellbore challenges. The quality check procedure would allow us to recognize valid tests and avoid making critical decisions based on false responses.