bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing Geosteering With AI: Integrating a Decision-Making Robot Into a Cloud-Based Environment and Benchmarking Against Human Experts
Authors: Muhammad Ressi Bonti , Cheraghi Yasaman , Alyaev Sergey , Srivastava Apoorv , Bratvold Reidar Brumer 
Published: April 2024

Abstract
This paper aims to demonstrate the application of a new automatic geosteering method that combines probabilistic interpretation with artificial intelligence (AI) for look-ahead decision-making. We expand on our previous synthetic workflow by integrating the geosteering "robot" into a commercial cloud-based geosteering environment through its web application programming interface (API). We bench- mark the robot against 100 active human participants of the ROGII Geosteering World Cup (GWC) 2021.
Our automatic geosteering method combines a Reinforcement Learning (RL) algorithm with the Particle Filter (PF) method. PF continuously assimilates real-time log measurements obtained during geosteering operations, producing hundreds of most likely geology interpretations. Simultaneously, RL uses the information gathered from PF outputs to optimize steering decisions. The robot implemen- tation automatically collects the new well trajectory and logs and passes the latest data through the PF. The RL uses the most likely interpretations to balance the short- and long-term steering priorities and outputs a single recommendation that the robot sends back to the cloud.
Our combined PF and RL ("PLuRalistic") method achieves a remarkable reservoir contact percentage of approximately 80 % for thin and faulty target layers in our synthetic environments. The "PLuRalistic" robot expands this promising methodology to the commercial cloud environment. As part of our results, we provide a detailed account of the integration process to the cloud environment via the Solo Cloud Python SDK. This SDK is the conduit for retrieving real-time log measurements and delivering automated decisions, enabling a closed-loop geosteering decision-making framework for GWC and real geosteering in the future. The operation of our robot significantly surpasses real-time operation requirements, making one steering decision in approximately 4 seconds, far below the two-minute-per- stand drilling time allocated for the GWC. With the adjustments of the robot to pre-drill geology and GWC operational constraints, it managed to achieve 74.8% percent reservoir contact and top-quartile performance among human geosteerers.
The fully automated decision-making robot represents a radical innovation in geosteering workflows. High-fidelity simulation of the GWC gives a unique opportunity to verify and improve the AI technology. More importantly, the simulated environment with tools familiar to experts allows testing and improving user-system interaction. In particular, we utilize population data from experts for the proposal distribution of geology for the PF and evaluation of the decisions generated by RL.
Shedding New Light on Old Problems, Understanding Why Conventional PDC Bits Struggle to Drill Soft Sand Formations in the Norwegian North Sea
Authors: Lunney Iain , Sturdee Dan , BP Aker 
Published: April 2024

Abstract
Whilst drilling development wells in the Norwegian North Sea over the last several years, significant drilling dysfunction in the form of bottom hole assembly (BHA) whirl has presented while drilling both the Grid and Skade sandstone units which resulted in trip for failures and non-productive time. These sandstone units form part of the overburden section and are laterally extensive across many fields in the Norwegian continental shelf. The historical consensus with regards to the causative mechanism was that the cleaner intervals of the sandstone units was being hydraulically enlarged by the flow exiting the bit and subsequently providing the bottom hole assembly room to move within the wellbore and develop damaging vibration mechanisms.
During a recent campaign of both exploration and development wells, the BHA whirl vibration mechanism once again presented itself where the occurrence was documented across a range of hole sizes, wellbore inclinations and drive types from rotary assemblies to rotary steerable tools. While the whirling dysfunction had caused non-productive time on historical drilling campaigns, there was not a documented root cause in place to clearly tie the dysfunction to wellbore enlargement.
After the initial instances of BHA whirl during the recent drilling campaign, a multi-disciplined investigation was initiated to evaluate the root cause of the drilling dysfunction in the clean Grid and Skade sandstone units where the corrective action was to re-evaluate the drill bit design criteria and hydraulic configuration. The data and interpretation presented in this paper will demonstrate that the source of the drilling dysfunction originates at the drill bit / rock interface and is not initiated by a mass-imbalance mechanism due to wellbore hydraulic enlargement. To conclude on the data interpretation, the stability benefits of a different bit type will be presented to demonstrate the effectiveness in eliminating bit induced whirl and the criticality of interpretating drillstring dynamics data inn both the time and depth domains.
The Effect of Bismuth Plug Expansion on Cement Sheath Integrity
Authors: Hmadeh Lewaa , Feneuil Blandine , Wiggen Even , Skorpa Ragnhild , Sangesland Sigbjørn , Elahifar Behzad , Anuncição Jaculli Marcelo 
Published: April 2024

Abstract
In the North Sea, around 2000 off-shore wells are scheduled to be plugged-and-abandoned over the upcoming decades, requiring new cost-effective solutions. Among those, bismuth alloy plugs are raising a major interest, as they have high sealing abilities and require less material volume than cement plugs. Bismuth is well-known for its expansion during solidification as its main sealing mechanism. In this work we investigate whether this expansion may damage the annular barrier material set behind the casing.
In this study, we examine a laboratory-scale well section composed of a sandstone rock (diameter 15 cm and height 20 cm), a 2mm thick casing, and a temperature-resistant silica-Portland G cement blend placed in the annulus and cured at 110°C for one week. The setup has been designed to allow for bismuth alloy placement in the casing and curing at relevant field conditions: 160°C and 60 bar. With an X-ray Computed Tomography (CT) scanner, we take 3D pictures of the sample with a resolution of 100 µm to evaluate the development of any cracks.
To assess the impact of bismuth expansion on cement and separate it from temperature and pressure effects, we conduct X-ray imaging at various stages. Initially, we image before placing bismuth where we examine the cement and rock for existing flaws, like voids and cracks, right after the cement cures. Next, we expose the sample to 160°C and 60bar with water inside the pipe to check whether the annulus cement can withstand the testing conditions, followed by imaging. In the third phase, we pour the Bismuth alloy into the pipe and leave it to cool at standard conditions. At this stage, the alloy is not expected to expand much in the radial direction. Following these initial scans, we remelt the alloy inside the pipe at 60bar and 160°C using an in-house designed test cell, and then take CT images after 8 hours of curing under 60 bar, and one after 4 days and another after 4 weeks. Finally, we perform a final CT scan after melting out the bismuth alloy to verify the integrity of the annulus cement.
In this study, we address a major concern related to bismuth alloy plugs, specifically, the impact of their expansion on the pre-existing well barrier materials such as the cement in the annulus. The findings of this study will be used to refine our experimental methodology at later stages in this extensive research and support the qualification process of bismuth alloys as an alternative sealing material in P&A operations.
Rock Type Modelling of a Heterogeneous Tidal Reservoir of the Tilje Formation
Authors: Fitzsimons D. , Johansen O. , Legler B. , Lubeseder S. 
Published: April 2024

Abstract
Heterolithic tidal reservoirs, like those of the Tilje Formation, are challenging to model. In addition to primary facies, diagenetic overprint adds to the heterogeneous character of the reservoir. A rock type modelling approach is presented to enable the use and integration of conventional core data, whole core computer tomography (CT) scans, wireline data and well test data to characterise the reservoir.
Whole core CT data oriented to image log has allowed paleocurrent data, depositional facies and rock types to be interpreted at very fine scale. The combination of these data allows a better understanding of permeability distribution and anisotropy.
Permeability for given porosity class can have several orders of magnitude difference. The best rock type has permeability in excess of 1000 mD due to the presence of chlorite coating around grains which prevents the development of quartz overgrowths expected at the burial depths of the reservoir (4.5-5 km TVDSS). Rock type with reduced grainsize and/or thicker chlorite coating have reduced pore throats reducing permeability to 10 to 100 mD. In the absence of chlorite coating permeabilities are below 1 mD.
Well test interpretation suggests the presence of barriers close to the well bore with good connectivity in alternate directions. It is not known if the barriers are due to sealing faults or due to depositional or diagenetic features. The geological model has been built to ensure that the heterogeneity observed in logs and core and the response from well test is captured to allow production and injection well scenarios to be tested.
Rock types have been classified on the basis of Rock Quality Index (RQI) which is related to both original depositional textures (sorting and grain size) and diagenesis. Once defined at the plug scale whole core CT scans have been used to propagate the rock type in cored intervals. The resulting rock type curve was then used as a training data set for machine learning algorithms to populate rock types in un-cored intervals. Permeability thickness (kh) from well tests has been used to quality control and calibrate the rock type model. Once propagated to wells a multi scenario 3D rock type model was built.
Revealing Complex Oil Water Contacts Driven by Faulting
Authors: Clegg N. , Paredes R. Ameneiro , Arcano N. Suarez , Krueger M. , Hermansen E. 
Published: April 2024

Abstract
Oil-water contacts in mature fields where injection water results in complex sweep patterns display rugose morphologies. Understanding the driving factors behind the distribution of fluids is critical to advance reservoir understanding and therefore better exploit the reservoir. Mapping fluid boundaries with electromagnetic (EM) tools and integrating the resultant models with independent logging while drilling (LWD) tools is the key to increasing interpretation confidence.
Deep EM LWD inversion allows mapping of resistivity boundaries in the region of 25 to 30 feet from the wellbore. In a perceived massive carbonate reservoir these boundaries are dominated by low resistivity water and high resistivity hydrocarbons. Mapping these fluids can reveal complexities in the reservoir architecture and lithologic variation which facilitates optimal well placement and improved reservoir understanding. Increasing the confidence in EM inversions through data integration increases the capability of higher resolution fluid distribution interpretations.
In this example, a series of small sub-seismic stepped faults are revealed in the EM inversion results. The stepped appearance of the reservoir with sharp contrast between high and low resistivity zones reveals the underlying small scale reservoir structure. This supports two controls on fluid distribution: faulting and lithology. In some cases, hydrocarbon saturated porosities with high resistivities are at identical true vertical depths (TVD) to water flooded low resistivity zones. Faults are exhibited by thin, high apparent angle, low resistivity streaks, suggesting water movement parallel to the interpreted fault plane. However, zones immediately adjacent to interpreted faults retain high resistivity, suggesting water movement perpendicular to the fault plane is impeded. The position of the structural elements can be supported by analysis of density image logs displaying the same high angle features and the fluid distribution from analysis of EM images which are independent of the inversion results. Integration of multiple independent measures from multiple tools and methods reveals the sub-seismic reservoir architecture in detail.
Understanding how complex structural and stratigraphic elements contribute to the distribution of fluids in a reservoir can help to define the controls on production-time fluid movement in complex systems. To adequately capture the resolution required for detailed fluid boundary interpretation, data acquisition programs must consider tradeoffs of depth-of-investigation and resolution. Assessment of production and water flooding controls at different scales demonstrates the strength of a holistic approach to data analysis and interpretation.
Performance Optimization of Water Injection Wells Using Autonomous Outflow Control Device Technology in Offshore Norway
Authors: Kvilaas G. F. , Moradi M. , Voll B. , Mortensen P. H. 
Published: April 2024

Abstract
Making good horizontal water injection wells is more challenging than making good horizontal producers, linked to the uncertainty around formation impairment (if no or limited clean-up) and the possible problem of "thief zones" that steal a major part of the injected water and deliver low sweep efficiency. Autonomous Outflow Control Devices (AOCD) can reduce the problem of "thief zones" and were piloted in a recent well in the Ivar Aasen water injector offshore Norway.
To limit injection into possible thief zones (or limit the chance of making such thief zones) normal ICDs, often used for injectors as well as producers, were installed in combination with the new technology that close at a certain differential pressure or injection rate. As a dual system, this should give quite an even injection along the whole well. Completion design studies were performed in both the full dynamic reservoir model and a simpler steady-state inflow/outflow wellbore modelling pre-drill. The completion design was finalized post-drill by quickly updating the model with the actual log data from the drilled well.
While tracers indicated a clean well after the initial clean-up, the well surveillance during injection logging confirmed injection along the entire completed interval of the wellbore. Also, a significant breaking point on the step-rate test (SRT) was observed which was different behaviour than what has been conventionally observed from the wells completed with non-AOCD completion.
Improved water management is key for many assets such as Ivar Aasen field. The first pilot installations of AOCD technology in Norway in this field demonstrated this technology could help to make better wells and improve sweep efficiency in difficult geological formations. This again improves the environmental measures such as power usage and the need for chemicals to treat injected and produced water.
Pyintegrity: An Open-Source Toolbox for Processing Ultrasonic Pulse-Echo Well Integrity Log Data
Authors: Viggen E. M. , Diez A. , Johansen T. F. 
Published: April 2024

Abstract
Many companies offer similarly designed wireline tools using ultrasonic pulse-echo measurements to evaluate barrier integrity in cased-hole wells. While these tools provide very similar data, different companies process their data using different algorithms, typically to estimate the pipe wall thickness and the outer material's acoustic impedance. While the algorithms themselves are public, no openly available software implementations are available. Therefore, we have developed an open-source software toolbox called Pyintegrity implementing many of these algorithms. In this article, we demonstrate Pyintegrity by applying its algorithm implementations to a well integrity log from the open Volve Data Village dataset. Our results demonstrate that it is quite possible to process data recorded by a particular tool using processing algorithms developed for use with other similar tools, and we find a good correspondence between the different processing algorithms. Comparing the results produced by the different processing algorithms lets us confidently identify certain features in some of the results as processing artifacts that do not reflect the physical state of the well.
Acceleration of CO2 Solubility Trapping Mechanism for Enhanced Storage Capacity Utilizing Artificial Intelligence
Authors: Ali M. , Hamdi Z. , Elochukwu H. , Musa S. A. , Bataee M. , Behjat S. 
Published: April 2024

Abstract
This paper conducts a thorough examination of the carbon dioxide (CO2) solubility trapping mechanism, a pivotal facet of Carbon Capture and Storage (CCS) technology crucial for enhancing storage capacity. Leveraging the capabilities of Artificial Intelligence (AI), our objective is to innovate and expedite the solubility trapping process. The overarching aim is to hasten the solubility trapping mechanism, thereby achieving heightened efficiency and storage capacity in CCS applications. To assess the potential acceleration of solubility during geological CO2 storage and appraise the field application of successful CO2 sequestration, a multitude of case studies is imperative. These case studies, encompassing various reservoir characteristics, are facilitated through the application of an artificial neural network (ANN). Specifically, we have developed an ANN model for geological CO2 solubility in saline aquifers. The training and testing of the ANN model were executed using data generated from a synthetic aquifer, focusing on solubility and its trapping index. Employing Python with TensorFlow, we conducted training and testing iterations, selecting the optimal model based on the calculated coefficient of determination (R2) and root mean square error (RMSE) values. The model successfully predicted the duration of the solubility trapping mechanism and storage efficiency. Our findings suggest that the ANN model serves as a valuable tool for forecasting storage effectiveness and evaluating the success of CO2 sequestration. In scenarios where conventional simulations fall short, our model may offer a viable solution.
Assessing Agricultural Vulnerability to Climate Change Through Dynamic Indexing Approach
Authors: SAHOO DIBAKAR , Moharaj Prasanta 
Published: April 2024

Abstract

The present study aims to enhance the methodology for assessing agricultural vulnerability in the context of climate change, focusing on the diverse districts of Odisha. Acknowledging that vulnerability is influenced by exposure, sensitivity, and adaptive capacity, our research refines traditional assessment methods by incorporating the growth rate and instability of vital performance indicators to evaluate the relative vulnerability of each district. A key innovation of this approach is the use of normalized indicators, weighted in accordance with the proportional acreage of major crops in each district relative to the state, culminating in a comprehensive vulnerability index through the aggregation of these weighted components. Our findings reveal significant variability in the vulnerability profiles across districts within the same agro-climatic zones, thereby necessitating state-level intervention through tailored “Location Performance Vulnerability” based adaptation strategies. These strategies, including early weather warning systems, development of new and early maturing crop varieties, and adjustment of crop planting dates, are crucial for mitigating the adverse effects of climate change on agriculture. The study's methodology and findings offer significant contributions to the field, providing policymakers and stakeholders with a district-specific framework for climate change adaptation. This approach is especially relevant for the international academic and policy-making communities, as it highlights the importance of localized adaptation strategies in the broader context of global climate change resilience.
JEL Classification: Q54, Q1
Influence of superabsorbent polymer (SAP) content, particle size and sodium silicate modulus on the performance of fly ash-slag paste filling materials
Authors: Ma Chenyang , Zhang Zhipeng , Tang Haotian , Li Weihao , Ma Wanlin , Liu Rentai , Fan Jianguo , Li Hongrui , Chen Mengjun 
Published: April 2024

Abstract

The use of solid waste cementitious materials in coal mining and mine filling applications has been limited by substantial volume shrinkage and inadequate hydration. This study explored the incorporation of a novel SAP to improve the workability of solid waste filling materials. We examined the impact of SAP content, particle size, and sodium silicate modulus on the workability and mechanical properties through fluidity, setting time, compressive strength, and drying shrinkage tests. The water absorption and release mechanism of the SAP, along with its effects on workability and mechanical properties, were investigated using nuclear magnetic resonance, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. Our findings demonstrated that optimizing the SAP content, particle size, and sodium silicate modulus significantly enhanced the workability, stability, pumpability, and compressive strength of fly ash-slag paste filling materials. Our findings offer insights for modifying and developing solid waste filling materials and executing practical mine filling projects.
Sickle Cell Disease: Populations and Policies, A Systematic Review
Authors: Pakhale Smita , Joseph Joanne , Alhabeeb Fatmah , Ambade Preshit , Falavinha Bruna , Jama Sadia , Yang Sarah , Chow Ryan , Shorr Risa , Mugamai Eman 
Published: April 2024

Abstract

Background
Sickle cell disease (SCD) affects over 30 million people and is most prevalent in sub-Saharan Africa, India, the Arabian Peninsula, the Caribbean, and North/South America. Globally, people with SCD disproportionately suffer premature deaths, hospitalizations due to acute complications, and significant multi-organ complications. Despite vivid similarities with Cystic Fibrosis (CF), clinical care and research is disproportionately minimal for SCD. Both CF and SCD are inherited, life-limiting, multi-system diseases; however, one mainly affects white people and the other Black people.
Objective
We aim to describe socio-demographics of SCD populations globally and highlight policy limitations and urgently needed changes to achieve equitable and just SCD care and research.
Methods
An electronic database search of Ovid MEDLINE (“sickle cell disease and marginalized people” and “policy in sickle cell disease”) was conducted for the period 1947 to May 2022. Additional information was obtained through Google Scholar, gray literature, and back references of relevant articles. Study selection and quality assessment was conducted independently in duplicate.
Results
Data were extracted from 137 articles, reports, and gray literature. We propose five main actionable items: 1) establish and strengthen national and international screening programs; 2) implement prevention and education programs; 3) enhance collaboration between stakeholders; 4) increase funding for SCD related research; and 5) promote new models for multidisciplinary care.
Conclusions
Globally, social, economic, geographical, and political factors affect access to comprehensive SCD management. Urgent policy changes are needed for equitable, inclusive, and just SCD care and research.