bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Unified Modelling Approach using AI based Probabilistic Method to Address Structural Uncertainty in Carbonate Reservoirs
Authors: Grover Anurag , Al Shamsi Saif , Ahmed J. , Al Mesmari Abrar , Sandjivy L. , Collet Mickael 
Published: November 2024

Structural uncertainty is the degree of variability or error in the interpretation of subsurface geology, especially the geometry and position of the reservoir. It affects the estimation of hydrocarbon volume and the design of the optimal field development plan. In complex and heterogeneous carbonate reservoirs, structural uncertainty can be significant due to factors such as velocity variations, seismic resolution, multiple scenarios, and human bias. Therefore, it is crucial to have a robust and efficient workflow to quantify and reduce structural uncertainty using all available data sources. One of the challenges in conventional structural uncertainty workflows is the reliance on deterministic methods that often produce a single or few scenarios based on subjective assumptions and manual adjustments. These methods are time-consuming, inconsistent, and difficult to validate. Moreover, they do not account for the uncertainty in the seismic data quality and processing, which can propagate and affect the reservoir model. A more rigorous and objective approach is needed to capture the full range of possible structural outcomes and their probabilities.
This study proposes an integrated stochastic structural workflow that leverages Artificial Intelligence (AI) techniques to generate multiple realizations of the reservoir structure and quantify their uncertainty. The workflow consists of four main steps: (1) generating an initial structural model based on seismic and well data, (2) applying an AI-based probabilistic method to estimate the combined uncertainty (horizon interpretation & velocity) and its impact on the depth conversion, (3) performing a stochastic simulation to sample the combined uncertainty distribution and generate multiple depth-converted structural models, and (4) evaluating the structural uncertainty ranges and their implications for the reservoir characterization, volumes {Gross Rock Volume (GRV) & Stock Tank Oil Initially In Place (STOIIP)}, and field development plan. The workflow is applied to a case study of heterogeneous carbonate reservoirs in the Middle East, and the results are compared with the conventional deterministic methods for capturing depth uncertainty.
Green Growth and Sustainable Development on the Way: A Case Study from Fracturing Campaign in South Sulige Gas Field
Authors: Ting Jin , Fuyang Wu , Qian Ma , Yifan Dong , Qiang Wang , Na Li , Guan Wang , Liang Zhao , Jing Hua , Shu Zhang , Yin Luo , Yunlong Fu , Chao He 
Published: November 2024

Abstract
The South Sulige gas field is located in the middle of the Mu Us Desert in Inner Mongolia, with an arid climate, sparse vegetation, scarce water resources, and a fragile ecological environment. As the main operator in this field, South Sulige Operating Company (SSOC), a joint venture company between CNPC and TotalEnergies, aims to accelerate its transformation to green growth and sustainable development by reducing water consumption and carbon emissions in the fracturing campaign.
This paper describes a novel flowback-water treatment process, which can quickly treat the post-fracturing flowback water onsite with satisfactory water quality, required treating rate, and minimized cost. The treated flowback water will be used for mixing guar gel and fracturing in offset wells of the same pad. In addition, a specially designed gas capture and recovery unit is installed on the wellsite. Natural gas could be directly discharged into the downstream production network during the well cleanup period. Furthermore, an attempt was also made to substitute a traditional diesel fracturing pump with an electric-drive fracturing pump using the state grid.
Reuse of flowback water can reduce water consumption and waste disposal, which is critical for deserts and grasslands. Unlike the simple practice of treating flowback water to mix slickwater for pump-down in the adjacent blocks, remixing guar gel is required to place a high concentration of proppant and thus keep high post-fracturing production performance. The laboratory analysis result shows that the key ions in the treated flowback water meet the requirement for mixing gel. The core damage test also shows an equivalent level between treated flowback water and clean water. The maximum daily treating rate for one treating package was 700 m3/day and clean fluid yield rate was 80%. The yearly flowback water reuse ratio reached 40% and roughly saved 14% of the entire water consumption. On the other hand, a large volume of natural gas was captured after the special recovery units were utilized for a total recovery time of 5073.8 hours in 2023. Also, electric-drive fracturing pumps were used in 58 wells, which was 47.5% of the yearly work scope. These efforts resulted in approximately 76,900 t carbon emission reduction for the last fracturing campaign.
In the development of a tight gas field, to produce industrial gas flow from target wells, hydraulic fracturing is usually required. With more attention paid to environmental protection worldwide, how to balance project profitability with resource consumption and carbon emissions has become a critical consideration in the hydraulic fracturing domain. The practices described in this paper may be well adapted to other blocks with similar development features.
Chemical Remediation of Excessive Water Production
Authors: Othman A. , Ali A. , Kamal M. S. , Aljawad M. S. , Al-Ramadan M. 
Published: November 2024

Abstract
Excessive water production in oil wells diminishes their operational lifespan and presents notable technical and economic problems, including corrosion, less oil production, and scaling. These challenges are addressed with chemical techniques such as polymer-gel treatments and nano-silica which isolate water pathways within rock formations. These systems form gels upon contact with water but disperse when exposed to oil. The primary objective of this work is to develop polymer and nano-silica gels and compare their performance at reservoir conditions.
In this paper, we conduct a comparative study of two systems used to remedy the wells with excessive water production. Rheology and visual inspection are employed to assess the gels and gelation time formed by both systems. Various formulations of emulsified polymer-crosslinker and nano-silica systems, are inspected through rheology and tested in core flooding experiments. The better emulsifier is selected and added before the polymer, to help in diverting the mechanism to the water zone. The emulsifier tends to form emulsion and raise the viscosity of the oil zone. Then the pH of the system rose followed by the addition of polymer and crosslinker. In the nano-silica system, the breakers and activators are assessed to get the efficient system used in the study. Improved systems are proposed and tested alongside oil to explore breaking mechanisms. Then, core flooding experiments were conducted at 94 °C, 2000 psi confining, and 400 psi back pressure to evaluate the efficiency of the old and improved systems.
The visual and viscosity experiments identified the optimal concentrations of copolymer and nano-silica, tested both with and without oil, and suggested a better replacement. Based on the rheology results, appropriate concentrations of the activator and breaker were recommended for each temperature level to be used in core flooding evaluations. In these experiments, the selected concentrations significantly reduced water production across all types of core plugs tested. Following treatment, the emulsifier polymer crosslinker and nano-silica have a specific range of maintained structural integrity under varying temperatures and pressure differentials. The proposed system combination effectively inhibited water flow in different types of core samples by gelling the water zones and filling fractures and pores that directed water flow.
Both proposed systems impede water flow while forming emulsions with oil, which allow the passage of oil. However, the long-term integrity needs to be assessed to have a better view of the system, besides the cost of the two materials. This study emphasizes the viability of different innovative systems as a practical chemical solution to manage excessive water production in oil wells with significant pore openings.
BOP Pressure Chart Analysis Using Computer Vision Technology
Authors: Al Hosani Ali Mohamed Sayyar , Selvamoorthy Geetha , Kumar Koushik 
Published: November 2024

Abstract
A blowout preventer (BOP) is critical safety equipment in drilling operations, designed to prevent the uncontrolled flow of liquids and gases. BOP systems require inspection and testing at least every 14 days, with a pressure test conducted to ensure their condition. This test currently involves manually decoding pressure chart data from a mechanical pressure chart recorder, a time-consuming process. Our solution automates this by capturing the image of the pressure chart and decoding it using AI image analysis.
The application integrates with an existing BOP Inspection application. The drilling supervisor takes a picture of the pressure chart, which is then processed by an image processing algorithm. The solution includes techniques like grid and trace splitting, color detection, trace pixel classification, template detection, text extraction and recognition, template matching, outlier removal and pressure value analysis.
This automation saves an average of 90 minutes per test for the drilling supervisor and improves the accuracy of pressure test reporting. Applied across ADNOC Onshore rigs, it has shown an estimated 300% ROI. The extracted data is exported in JSON format for integration with existing applications.
This paper presents a novel application of AI in computer vision for automating this pressure chart data extraction, demonstrating significant efficiency gains and a high ROI, adding value to the petroleum industry's body of knowledge.
Effect of Fracture and Vug Network on the Dolomite Carbonate Acid Stimulation Process
Authors: Jia Cunqi , Alkaabi Saif , Hu Jinchuan , Sepehrnoori Kamy 
Published: November 2024

Summary
Acid stimulation in carbonate rocks represents a classic example of reactive flow in subsurface porous media and is also an extremely effective improved oil recovery technique with broad applications. The acid solution is injected into the formation under the formation fracture pressure to increase formation permeability while bypassing damaged domains around the wellbore. This work extends an integrated two-scale continuum model that contemplates mass, momentum, and energy changes to study the acid stimulation process in complex carbonate acid stimulation systems with the development of fracture and vug networks. Numerical examples are designed to examine the impact of isolated fracture and vug parameters on the results of acid stimulation. Results show that the improved two-scale continuum model offers a novel method for describing the momentum transport of fluids within complex media. It eliminates the necessity of introducing and determining additional physical parameters through numerical simulations and experimental research. The presence of isolated fractures and vugs has a limited contribution to the hydraulic parameters of permeability. Isolated fractures and vugs reduce the consumption of acid fluid required to break through the target core sample but do not change the optimum injection rate for wormhole formation. The development of fractures and vugs can guide the development pathways of wormholes within the matrix core but does not alter the dissolution patterns corresponding to the specific acid injection rate.
Tank Level Monitoring Using Thermal Video Processing Model
Authors: Korjani Mehdi , Ramezani Elena , Chung Jae Yoon , Conley David , Smith Mark 
Published: November 2024

Abstract
The conventional method of using liquid-level sensors like guided wave radar (GWR) for liquid level detection in oil tanks poses significant safety and environmental concerns. The process of opening the tank hatch for maintenance and calibration exposes workers to hazardous gasses and increases the risk of explosions. Additionally, the release of harmful substances during calibration contributes to environmental pollution. To address these challenges, we developed a non-intrusive approach using thermal video processing model as a safer and more environmentally friendly alternative to GWR.
The model utilizes thermal videos captured by a thermal camera and employs advanced deep Learning image processing techniques to detect thermal differences between the full and empty parts of the tank. By accurately estimating the liquid level based on these thermal patterns, the non-intrusive approach eliminates the need for physical access to the tank, thereby mitigating safety risks and minimizing environmental impact.
The performance of the thermal video processing model is evaluated by collecting data from multiple tanks and comparing the results with those obtained from guided wave radar. We evaluated the model in different edge cases including different weather conditions like snow, storm, rain, and also different temperatures. We also evaluated the model in shadow, camera shake, and blocking objects like tanker trucks, pipes or other tanks.
The results of this work demonstrate that the thermal video processing model achieves comparable accuracy to guided wave radar for liquid level detection in oil tanks. The model successfully identifies and differentiates thermal patterns with more than 94% accuracy, enabling precise estimation of the liquid level with 98% accuracy. By eliminating the need to open the tank hatch, this method ensures worker safety by minimizing their exposure to hazardous gasses and reducing the risk of explosions and release of harmful substances to air.
The deep learning video processing model performing tank level detection is very robust to edge cases including different temperature or weather conditions. It is also very resilient to shadow during the day and can detect levels even when less than 10% of the tank is visible. The findings demonstrate the potential of thermal image processing as a viable and efficient approach, offering a safer and more sustainable solution for the oil industry.
Leveraging Neural Radiance Fields for High-Fidelity 3D Digital Outcrop Reconstruction and Characterization
Authors: Agbor Yannick , Tishechkin Dmitriy 
Published: November 2024

Abstract
This study continues SPE-216868-MS and adds a novel application of Neural Radiance Fields (NeRF) for digital outcrop modeling and rock characterization. NeRF as an open-source AI/ML framework, enables the synthesis of high-fidelity 3D reconstructions from 2D images. We leverage NeRF to create the high-fidelity, real world 3D scenes of the rocks and outcrops. We use a combination of field observations, photographs, and LiDAR scans to create a large dataset of outcrop samples from various locations. Our methodology consists of three main steps: data preprocessing, training an optimized NeRF model, and analysis of the resulting outputs. In the first step, we preprocess and align the collected imaging data to ensure consistent lighting conditions and remove any noise and artifacts. Next, we train the NeRF model using the preprocessed data, which enables us to reconstruct the 3D geometry and appearance of the outcrops. Finally, we analyze the trained models to extract rock features, such as texture, porosity, permeability, and mineralogy. Multi-view geometry and incorporated physical constraints reconstruct the 3D geometry and appearance of the rock sample.
This use case and the workflow above demonstrated how the subsurface data can be made accessible to the broad audience, independent of its technical proficiency or familiarity with the specific region of the data itself. The whole workflow is designed with almost no coding, chaining together open source tools with easy-to-use no-code interfaces on the cloud. Once the initial solution is setup, it is also easily extensible to additional scenarios and data types. The solution saves engineer’s time and resources and leads to more accurate geological interpretations and increased exploration success. By integrating multi-view geometry and incorporating physical constraints, our method faithfully reconstructs the 3D geometry and appearance of the rock sample, capturing intricate features at sub-millimeter scales. This rock models can be taken further to the numerical simulations or AI/ML models to calculate various reservoir properties such as fluid saturation, pore pressure, and more.
Overcoming Practical Artificial Lift Challenges to Produce Extra-Heavy Oil from a Deep Reservoir in Northern Kuwait
Authors: Al-Murayri M. T. , Akther S. , Baroon B. , Soltani A. , Garifullin R. , Delamaide E. , Rousseau D. 
Published: November 2024

Abstract
Extra-heavy oil reserves in the Abdali field in Northern Kuwait exhibit a viscosity ranging from 6,000 to more than 15,000 cP at depths of ~9000 ft. Assuming a fully isolated tubing, the theoretical natural flow rate is less than 1.0 bbl/d. The viscosity profile shows an exponential trend inside the well reaching millions of centipoises at surface conditions. This paper investigates the lifting challenges and possible solutions for the efficient, practical and commercial production of these reserves. The study builds upon the findings presented in two previously published papers by Al-Murayri et al. (2024).
A compositional EOS with a Pedersen (1987) viscosity model was used to accurately describe the properties of the oil, liquid solvent, and their mixture at different pressures and temperatures inside a vertical well. A correct fluid property description from PVT flash calculations was key for modelling the weight of the column, friction losses and the pressure distribution along the well.
Jet Pump and ESP were considered. Other pumps were discarded either because of their incompatibility with the reservoir depth or due to their environmental footprint. Nodal analysis combined with advanced analytical calculations and numerical simulations were necessary to find feasible operating points for different well configurations.
Abdali's oil must be diluted with liquid solvent at the bottomhole to reduce the viscous friction losses. Adding 70% mass fraction of liquid solvent reduces in-situ oil viscosity from 6,300 cP to 9 cP, and the viscosity at surface conditions from 3,000,000 cP to 65 cP. The proposed Jet Pump used the liquid solvent as power fluid. Its configuration ensured the desired BHP and liquid rate with good efficiency. The key parameters were the ratio of power fluid to the reservoir fluid, the pressure discharge, and the pump Nozzle diameter. ESP lifting necessitates a concentric tubing or a capillary tube for liquid solvent injection. A direct solvent injection into the annulus showed higher than target BHP due to the cumulative impact of the hydrostatic solvent column weight and the topside injection pressure. For the capillary tube, Bernoulli's equation proved that the hydraulic weight of the column is partially compensated with friction losses resulting in the desired BHP. It was shown that numerical simulations are necessary for nodal analysis of such a complex lift design.
Prominent industrial well modelling packages cannot handle extra-heavy oil blends with liquid solvents due to a lack of EOS integration in their artificial lift design. This paper investigated a novel approach combining advanced analytical calculations with nodal analysis and numerical simulations to prove the feasibility of lifting a complex fluid mixture from a deep reservoir while capturing the flow dynamics from the bottomhole to the wellhead.
Empowering Frontliners to Work Effectively for HSECES Equipment Through Introducing Cost-Effective E-Inspection Digital Solution
Authors: Alzahmi Abdulazeiz M. , Mohammed Abdalla O. , Khateri Abdulla A. Al , Nadakkavil Noufal 
Published: November 2024

Abstract
The essence of maintaining Health Safety Environment Critical Equipment & Systems (HSECES) is paramount for the safe operation of production facilities. The HSECES management standard necessitates that minimum assurance tasks (MAT) for each HSECES category or tag level are performed and documented to confirm that the HSECES are functioning correctly and as intended. Historically, the process for executing MATs or HSECES maintenance jobs during planned maintenance was unsystematic, with data being uploaded to SAP as handwritten scanned documents or Excel files, resulting in poor data quality and inconsistency.
This paper presents a novel solution: a mobile application that integrates seamlessly with SAP, enabling frontliners to record MAT or HSECES maintenance job results directly on-site and automate the workflow approval process. Additionally, a web application is included for viewing, completing, approving, and generating automated MAT reports summarizing the maintenance activities with the assurance value for each related tag. The web application also acts as a data repository, storing all historical HSECES data for further review and analysis. The solution was developed internally, utilizing existing resources (connected worker devices and PCs), and incurred no initial costs.
The implementation of this solution has eliminated the need for paper printouts, thereby reducing environmental waste associated with maintaining critical equipment. It has simplified the process flow for frontliners, improving their efficiency and freeing up their time for other tasks. The digitization of essential processes has led to better record-keeping and opened up possibilities for detailed analysis and integration with other systems.
Furthermore, the solution includes additional features that enhance HSECES management, such as automatic notifications, the ability to capture missed HSECES tags, and the capability to update minimum assurance tasks instantly across company sites. This solution exemplified a progressive approach improved frontliner effectiveness, automated essential processes, and promoted a greener environment.