bluuebunny/crossref_metadata_2025 huggingface dataset:
O que são os quadros psicóticos?
Authors: Silva Antônio Geraldo da , Martins Cláudio , Brunoni André , Cordeiro Quirino
Published: February 2024

No dia 21 de fevereiro de 2024, o presidente da ABP, Dr. Antônio Geraldo da Silva, recebeu os psiquiatras Cláudio Martins, André Brunoni e Quirino Cordeiro em uma live para debaterem "O que são os quadros psicóticos?".
Cyclic forms as a way of presenting existential issues in A. M. Remizov's story "Sisters of the Cross"
Authors: Demidov Nikita Mikhailovich
Published: February 2024

The article analyzes the forms of cyclization in the story "The Sisters of the Cross" by A.M. Remizov and their role in the realization of the existential problematic of the work. The originality of Remizov's creative consciousness and artistic method, his interest in the ontological foundations of personality are emphasized by a special narrative structure, which is characterized by the strengthening of the corresponding motional structures. The religious and mythopoetic understanding of reality, inextricably linked with the artistic method, allows us to talk about the cycle as a broad category, according to the concept of I. Pospisil, which implies, along with motives, the unification of various forms of lexical and semantic repetitions in order to actualize important issues of being for the writer. The author of this article believes that the logic of the writer's strategy and its embodiment in the composition of the work are unthinkable without understanding the elements of the cycle as contextually updated units of content that need active interpretation by the reader, which is necessary for a holistic perception of the work. This understanding of the cycle is complicated by the grotesque characterization of the motifs and their correlation with both the metatext of Remizov's early work (the concept of the "artistic ensemble" by E. Tyryshkina) and the metatext of the Russian novel, the evolution of the plot structure of which is associated with the complication of the existential aspect. Based on the tasks set, the article uses structural-descriptive and descriptive-functional methods to analyze the system of cyclic forms of the writer and their functions. Taking into account the large-scale content coverage of the existential issues in A. M. Remizov's novella "The Sisters of the Cross", when considering the forms of cyclization in the work, it is necessary to take into account not only the hierarchical levels of the text (lexico-semantic repetitions and motivic structures as part of the composition of the story itself and from the point of view of the metatext of Remizov's work) and the different functions of these forms, but also common features cyclical trends in the narrative. Thus, one of the aspects of Remizov's poetics receives a proper theoretical understanding. The analysis of the story shows that a broad understanding of the cycle allows us to group the heterogeneous elements of the composition in terms of their general content orientation, which in further research may be useful in a holistic analysis of Remizov's work, his writing strategy, as well as the author's place among other masters of ornamental prose in Russian literature.
Sprawozdanie z sympozjum wykładowców liturgiki
Authors: Kopacz Iwona
Published: February 2024

W dniach 12-14 września 2023 r. w Prymasowskim Wyższym Seminarium Duchownym w Gnieźnie odbyło się 58. Sympozjum Wykładowców Liturgiki na Wydziałach Teologicznych i w Wyższych Seminariach Duchownych. Zgromadzeni podjęli temat: MYSTERIUM – ACTIO – VITA. Wokół teologii i liturgicznej praxis Benedykta XVI.
Online Sequence-Based Deep Learning Approach for Metallic Debossed and Embossed Turbomachinery Blade Text Recognition Application
Authors: Youssef A. , Mishra P. , Vitale M. , Schillaci G. , Veneri G. , Bettini A. , Anatriello G. , Burbui M. , Ceccherini F.
Published: February 2024

Extracting the engraved characters of metal parts in the industrial sphere remains a challenging task due to low visual contrast, uneven illumination, corroded surfaces, and cluttered backgrounds of metal part images. Affected by these factors, generally existing methods could not identify low-contrast text areas very well. Furthermore, the task is complicated by the fact that the embossed and deposed text can have a wide range of appearances, including variations in curvature, orientation, and distortion, which makes it more difficult to accurately recognize the text. In this paper, we investigate a sequence-based approach consisting of detection and recognition deep learning models for blade text recognition. These models are integrated into a feedforward pipeline that segments, detects, and recognizes embossed and debossed imprinted text on metal surfaces. The text localization model utilizes a U-shaped network with a VGG-16 architecture for feature extraction. On the other hand, the text recognition model is an end-to-end convolutional neural network designed for image-based text recognition, capable of handling arbitrary sequence lengths and orientations.
Modeling the Effect of Transient Viscous Forces on Sucker Rod Pump Performance and Run Lift
Authors: Aql A. A. , Al-Safran E. M.
Published: February 2024

The sucker rod pump is commonly used to lift heavy oil wells under thermal production to maximize the flow rate due to its high efficiency and reliability. However, rod fatigue and possible failure are commonly encountered when rod design does not incorporate the appropriate loads, especially in high-viscosity conditions. Although the existing commercial design tools solve the wave equation to predict rod string life, they do not incorporate the effect of liquid viscosity, resulting in prediction discrepancy and inappropriate rod design and pump operation. The aim of this study is to propose a theoretical model to investigate the effect of the transient frictional forces acting on sucker rod pump subsurface components, i.e. rod and pump. Furthermore, a sensitivity analysis case study is carried out to investigate the effect of various flow and design parameters on the rod top-of-section stresses, rod buckling tendency, and fatigue life. This work provides a comprehensive understanding of the underlying interaction between fluid flow behavior and rod dynamics.
Cased-Hole Saturation Tool is Crucial for Optimizing Production and Reducing Uncertainties in a Naturally Fracture Carbonated Reservoir, Offshore, Libya
Authors: Grada Abdurahman , Ahmed Hamza , Elgihani Anis , Almalti Abduallah , Imhimmid Abdulrraziq , Mansour Kareema , Mohamed Nureddin , Mohamed Mnani
Published: February 2024

Bouri Field is an offshore saturated oil-bearing structure. The reservoir is a fractured carbonated deposit, and during production, gas and water are moving into the oil zone at the top and bottom, respectively. Consequently, monitoring the contacts is essential to optimizing field production. Unfortunately, the Gas-Oil contact (GOC) remains an uncertain parameter which directly impacts the selection of the targeted zone. Since the gas is flared out and limited gas capacity is allowed in the surface facilities, therefore, reducing gas production is essential. In addition to gas production issue, many wells stopped producing because of high water cut. At the early stages of the production history, the reservoir pressure was high enough to enhance lifting the fluid naturally all the way to the surface. However, some wells struggle to flow naturally when the reservoir pressure gradually decreases. Even though, there are many reasons behind the high-water production, nevertheless, understanding the Oil-Water contact (OWC) will be extremely valuable in managing the undesired water. This paper presents work has been done to evaluate the current field contacts by performing cased hole saturation logging tool to optimize production and reactivate shut-in wells to a number of 17 wells in Bouri field.

Well by well analysis was carried out to assess the field potential. The thorough evaluation included reviewing the wells events and operations, production and pressure history, fracture signatures, water production analysis. Considering set of criteria, a systematic approach was followed to select the key wells to be used for the saturation logging campaign to identify the regional contacts. These contacts will be an essential input to the workover program to mitigate the damage and control the unwanted water.

As a result of the study, five wells were chosen for the saturation logging campaign. The campaign revealed a dramatic change in the contact. In some areas, the OWC has raised and covered considerable interval of the reservoir thickness. While in other areas, the gas has expanded and found its way to the perforation. By correlating the saturation profiles form the key wells, the oil zone was identified along the field and a perforation, water shut-off and stimulation campaigns were proposed accordingly. A acritical water cut was which above the wells cannot produce naturally was detected around 60% to 80% depends on the wells’ locations. Three wells considered for Electrical Submersible Pumps (ESP) to extend the wells life and maintain the production.

It was recommended to perform borehole images to understand the fracture locations and density to be considered for any fracture network analysis. Building an accurate simulation model is another reason to update the saturation profile of such complex field.
Advanced Production Diagnostics and Optimized Drilling Strategy: Unlocking the True Potential of Production Data Using Physics and Machine Learning
Authors: Haider S.
Published: February 2024

Reliable well survival statistics forecast for shale wells is crucial for investment decisions, optimized drilling rates, and energy security policies. At present, the industry lacks a standard analytical or data-driven solution for survival probability estimation in both space and time. We present a state-of-the-art physics-guided and data-driven model for well survival statistics forecast with an error of less than 5%. The implications include optimized long-term drilling strategy, robust well production diagnostics, and profitable economic decisions.

Post pressure interference time, τ, the production rate of an unconventional well declines exponentially. Early and accurate estimation of τ is of utmost importance. Using 5000 wells (from Barnett, Marcellus, Haynesville, and Eagle Ford) as the training sample, we developed a universal neural network model to estimate the pressure interference time, τ, of a well. The estimated τ is coupled with the physics-based physical scaling curve to estimate the well survival statistics with time. Finally, the well survival statistics is used to calculate the residual production rate and its consequences on future well fracking strategy.

The robustness of the neural network model (ANN) is tested on a test set comprising 6000 wells from Barnett, Haynesville, Eagle Ford, and Marcellus. Using initial well production data, and a single ANN model the predicted pressure interference time τ, has an R2 of 0.98. The well survival statistics estimates for the next 10 years in the future achieved an accuracy of 95%, 93%, 96%, and 95% for Barnett, Marcellus, Haynesville, and Eagle Ford respectively. We found that with time τ has decreased for all the plays (Barnett, Haynesville, Eagle Ford and Marcellus). The estimated well survival statistics is shown to have a strong effect on the optimized and profitable drilling strategy.

We have used production data and a physics-informed neural network to unlock future production diagnostics with high certainty. The new and robust state-of-the- art hybrid model estimates the future pressure interference time of wells with an accuracy of 98%. The model calculates the future well survival statistics with time with an average accuracy of 95%. Early and accurate estimation of future production diagnostics governed future investment decisions, re-fracking strategy, and improved energy security strategy.
An Ultra-High Temperature New Microemulsion Technology for Deep Drilling Wells: Lab Study
Authors: Al-Saqer Qassem , Alabdulmohsen Zainab , Anioke Chidiebere , Al Qunis Mohamed
Published: February 2024

Formation damage caused by reservoir drill-in fluids or completion fluids could be minimize by microemulsion fluid system in an average reservoir temperature. However, in deep drilling wells the formation temperature can reach up to 380 °F, which requires a new design that can tolerate this level of temperature with minimum formation damage.

This paper presents an engineering approach on overcoming the formation damage in ultra-high temperature reservoirs. The new microemulsion fluid design contains a low organic acid concertation, and a surfactant blend that can stand for high temperature formation. The surfactant blend has a high capability of removing the filter cake residues and water wets all solids surfaces. Extensive laboratory work conducted to demonstrate this approach by studying the properties of the new fluid design on both drill in fluids and oil-based muds with high and low gravity solids through filter cake removal efficiency test and multi – stage back flow test.

For both fluids type, drill in fluid and oil-based mud with high and low gravity solids, results showed more than 60% filter cake removal efficiency and 83% improvement in return to flow value for OBM with high gravity solids and more the 90% filter cake removal efficiency and 96% improvement in return to flow value for drill in fluid when using the new surfactant in comparison with current used surfactant. The organic acid in the microemulsion blend removes the formation bridging solids, while the high gravity solids are dispersed and mobilized when circulated. This blend shows a high capability of removing the filter cake residues and water-wetting solid surfaces, which leads to reduce the near wellbore damage and increase well productivity in both oil and gas production formation.

The new microemulsion solution has an ultra-low interfacial tension property that helps with the diffusion of the project into the rock matrix and lead to solubilizing the oil in the filter cake emulsion while converting the solids and surfaces in a water-wet state.
Innovative Method to Predict H2S Concentration from Advanced Mud Logs
Authors: Qubaisi Enter: Khalid , Meridji Yacine , Rubaie Naif , AlAkeely Abdullah
Published: February 2024

Hydrogen Sulfide (H2S) presents a hazardous environment while drilling. Measuring H2S concentration real-time while drilling will provide early indication and allows the operator to the necessary safety precautions at the rig site and ensures proper execution of rig operations. There were several attempts in the oil and gas industry to estimate hydrogen sulfide, yet there's no proven methodology to accurately measure H2S concentration real-time while drilling. Mud Logging services, also known as surface data logging can be utilized to predict H2S concentration while drilling. Although Mud Logging does not actually measure H2S directly, some of the actual measurements can be used as proxies to predict H2S concentration.

Common practice is to acquire PVT samples and/or perform Drill Stem Test (DST) to quantify fluid properties and have an accurate measurement of H2S volume. Our innovative methodology that will be discussed further revolves around building a predictive model that can estimate H2S concentrations prior to sample acquisition to ensure proper and safer sampling or testing procedure. The model is trained on few wells where DST tests were performed and an actual H2S concentration is known, then the model is deployed on few blind tests to investigate model validity and accuracy. Several iterations were made to select the best inputs from Advanced Mud Logging (AML) logs to best predict H2S % in the reservoir rocks. Furthermore; multiple regression methods were tested to achieve optimum modeling. The CNN (Conventional Neural Networks) model delivered the lowest RMSE (Root Mean Square Error), therefore was identified as best modeling technique.

Several inputs from AML logs were selected to build the predictive model: Methane, Total Normalized Gas, Volume of Calcite, Volume of Dolomite and CO2 (Carbon Dioxide). The model indicated that there was a very strong correlation between AML outputs and H2S concentration with Normalized total gas showing the highest correlation followed by C1 gas (Methane). Interpreting potential in-situ H2S can lead to taking the necessary precautions at the rig site. Using advanced mud logging can not only identify zones of interest but can also act as an early warning system for potential drilling hazards. Workflows are placed to identify these potential H2S accumulations that can pose a risk to operations, downhole tools, and forward testing procedures can be planned accordingly.
Emphasis of High Order Stratigraphic Sequences Enabled by the Relative Geological Time Modelling Method: Application to Fractured Thin Reservoirs in a Pre-Salt Gas Field, Offshore Netherlands
Authors: Daynac N.
Published: February 2024

The author describes the method and results of a global and automated approach for seismic interpretation (Pauget et al, 2009), applied to a pre-salt gas field of the Dutch Cleaver Bank High platform, offshore Netherlands. A sequence stratigraphic framework called ‘Relative Geological Time (RGT) model’ is built from the seismic data to emphasize structural and stratigraphic features. Basin and reservoir characterizations are thus enabled by RGT-derived advanced attributes, rock physics modelling, Wheeler diagrams and sub-sample stratal slicing. Several fault networks related to different tectonic phases are emphasized, key stratigraphic surfaces are delineated, and major facies trends of the pre-salt reservoir level are discriminated. Those outputs are finally used to assess the impact of fault networks and subsequent subsidence on the eustasy-controlled thin beds succession. The author ultimately demonstrates the potential of the global RGT modelling method to revise hydrocarbon fields and identify pre-salt siliciclastic carbon storage sites.
Rock Physics Modeling and Iterative Petrophysics Driven Inversion Results: Estimating Subsurface Petrophysical Properties and Characterizing Reservoirs - A Real-Time Case Study of Clastic Gas Field in Pakistan
Authors: Azeem Adil , Hameed Ali , Ali Virk M. Muneeb , Awan Faheem Razzaq , Mathur Akash , Abid M. Faraz
Published: February 2024

Rock physics modeling (RPM) using iterative petrophysics is a vital tool in the oil and gas industry for predicting subsurface properties and characterizing reservoirs. This technique has revolutionized the way in which analysis and interpretation of seismic inversion data has been performed and provided better understanding of the subsurface geology. The main scope of this work was to highlight the importance of using RPM logs data as opposed to using directly recorded and linear regression based corrected logs for seismic inversion input.

The approach that was followed for this study started with building a consistent RPM based upon the iterative petrophysics. The results of RPM data were compared with recorded and multi-linear regression (MLR) data-set. The main quality check for the health of the well log data was set to see which data will provide a closer correlation to the original seismic amplitude versus offset (AVO) response. Using well to seismic tie of RPM and recorded well logs data, the well based wavelets were extracted and compared. Moreover, the pre-stack inversion was performed with the optimized parameters. Furthermore, consistent well based probability density functions (PDFs) for two different facies were generated and implemented on the inversion results. Finally, the results were quality assured on the blind wells.

It was concluded that, the well based elastic logs response were improved dramatically using RPM and iterative petrophysics approach. The modeled AVO response (intercept and gradient) of the RPM based data was much closer to the original conditioned seismic data as compared to data from Multi-linear regression (MLR) and original recorded logs data. RPM data provided a far better well to seismic tie, an average cross-correlation improvement from 50 to 70%, resulting in a consistent well based wavelet. In addition, this led to improved PDFs and implementing them to the pre-stack inversion results. Furthermore, the correlation of the predicted litho-facies at the blind wells were consistent with the encountered petrophysical properties.

This study highlights the importance of RPM and iterative petrophysics as a vital tool for oil and gas industry. Current study not only highlights their importance but also highlights importance of effective reservoir characterization with enhanced seismic data interpretation, robust well-ties and accurate porosity and litho-facies away from wells. These insights not only have a huge impact on reservoir monitoring and management but also crucial for strategic decision in the industry.
A Study in Ultra-Thin Cement Sheath Evaluation
Authors: Li B. , Olaiya J. , Garcia M. , Kamgang S.
Published: February 2024

Reliable evaluation of the cement-bonding and identification of isolation zones of a cased-hole well are challenging problems. The CBL tool can provide a cement map for identifying cement top and cement channels of a well. Ultrasonic tools have been developed and deployed to conduct pitch-catch and/or pulse-echo measurements for cement evaluation at high spatial resolutions. However, there are limitations in tools based on pitch-catch or pulse-echo measurements, particularly for ultra-thin cement sheath.

This paper presents a systematically study of effects on responses of sonic and ultrasonic cement evaluation tools caused by cement sheath thickness and propose a workflow for the reliable evaluation of ultra-thin cement sheath. To quantify limitations of these types of cement evaluation tools, a systematically study has been conducted to evaluate effects caused by casing annulus spacing on tool responses. The test fixtures with varied annulus spacings were designed, constructed, and cemented. Multiple tests were designed and conducted to verify the annulus spacing effects on amplitudes of arrival wave peaks, the inverted acoustic impedance of casing annulus, attenuation rates of waveforms and quantify the annulus spacing size limits that cause the failures of tools. The tests results confirmed the attenuation rates of shear horizontal wave measurements will not be influenced by casing annulus if it is greater than 0.4 inch. The cement sheath must be greater than 0.75 inch if a CBL tool is utilized. For the first time, different types of cement evaluation tools are evaluated on the same test fixtures. This experimental study provides a guideline for selecting tools to conduct cement evaluation.
Development of Powder and Fiber Temporary Plugging Agent System to Improve Fracture Complexity in Slickwater Fracturing
Authors: Cao D. , Kalgaonkar R. , Huang T. , Baqader N.
Published: February 2024

Increasing fracture complexity by temporary plugging agent (TPA) in slickwater fracturing is getting great attention due to the huge difference with conventional fracturing. A powder and fiber TPA system was developed for narrow and long fractures in slickwater fracturing. Additives were optimized to improve the performances in both near wellbore and far field applications for unconventional reservoir developments. Three different powder and fiber systems with similar size were evaluated. For all the three systems, blocking efficiencies increased with injection flow rates. Weight ratio of 4:1 between powder and fiber showed much higher blocking efficiency than that with less fiber component. Samples S1 and S2 showed better performances than sample S3. The dispersibility of powders and fibers in slickwater was found critical to its plugging performance by a cross-sample test. Accordingly, two additives were developed to adjust the dispersibility of TPAs for improved performances. One additive improved migration ability of TPA system at high flow rate and plugging ability at low flow rate, which helped the TPAs flow through high flow rate near wellbore region to plug fractures in deep position. The other one was developed for near wellbore applications with enhanced plugging performance at both high and low flow rate regions. This work provides some insights of powder and fiber types TPAs to increase stimulated reservoir volumes for unconventional reservoir developments.
High-Resolution Characterization of Carbonate Source Reservoir Heterogeneity for Enhanced Production Optimization
Authors: Von Gonten W. D. , Ali S. , Ali M. , Eichman S. , Gupta A. , Kias E. M. C. , Mesdour R. , Al-Bassam M. , Degenhardt J. , Cordes M. , Suarez-Rivera R.
Published: February 2024

Carbonate source rock reservoirs often exhibit pronounced lamination, resulting in fine-scale facies and rock property variations that are not adequately captured by open hole logs. Precise characterization of reservoir heterogeneity across multiple scales is essential for accurate hydraulic fracture design, landing zone optimization, and ultimately enhancing well productivity. This paper presents a comprehensive workflow that utilizes specialized core-logging equipment to precisely define the thinly layered nature of the cored section, enabling centimeter-scale resolution analysis of vertical heterogeneity. The acquired data allow us to define distinct rock classes with unique and characteristics behaviors, based on multi-dimensional data patterns that mirror their unique and characteristic behaviors in rock properties. The rock classification facilitates the quantitative definition of vertical heterogeneity, capturing the fine-scale property variations within the core section. It also informs the selection of core samples for laboratory rock property characterization, ensuring that the representation of the observed variability is maximized. By integrating the multidimensional core-logging data with the discrete laboratory rock property results, we construct centimeter-resolution petrophysical and geomechanical models that result in higher fidelity reservoir characterization of thinly layered carbonate source reservoirs and more representative numerical simulations, thereby enhancing our ability to optimize hydraulic fracturing and well productivity. The workflow also includes upscaling the resolution of downhole wireline log measurements, utilizing image log measurements as structural constraints to the process, thereby enabling the derivation of high-resolution petrophysical and geomechanical properties in non-cored sections of the same well and in neighboring wells without core data. The study revealed cyclic reservoir and mechanical property variability, particularly in intervals with higher organic content, which were critical for understanding productivity, evaluating the in-situ stress, and for hydraulic fracture modeling. This level of detail in reservoir characterization is not achievable when using conventional resolution wireline logs.
A Novel Approach for Carbon Capture & Sequestration Pilot Study in the Western Desert of Egypt
Authors: Eleoni M. , Dredge J. , De Boer Y. , Mansour K. , Ismail A. , ElSayed R. , Merghany I. , Ellamey C. , Agam A. , Taqey A. , Gomes R. , Stojic S. , Nasiri A. , Bouchet F. , Nasreldin G.
Published: February 2024

Egypt, as the host for the previous UN COP27 in 2022, has committed to emissions reductions in support of limiting global warming. Carbon capture and storage (CCS) offers the potential to significantly reduce point source CO2 emissions in the country. Accordingly, the Egyptian operator BAPETCO, along with partners Cheiron and Capricorn, is exploring the potential for carbon capture and storage to sequester more than 350,000 metric tons of CO2 per annum.at two fields in Egypt’s Western Desert. Storage candidates comprise 20 stacked geological formations starting from Apolonia till Lower Safa, The objective of this paper is to present the novel methodology implemented to screen technically feasible and economically advantageous subsurface storage sites.

The applied approach is divided into three phases.1. The first phase is site screening, ranking, and selection to identify the best possible sites for CO2 storage. Through detailed geological characterization and modeling of all potential reservoirs within the two fields, specific sites are selected and ranked based on a scientific scorecard that is developed based on extensive experimental simulations worldwide.2. The sites with the highest rank pass to phase 2, the feasibility study. In this phase, selected reservoirs are reviewed in detail to quantify the reservoir capacity, optimize injection scenarios, confirm the required well count, and propose injection points. The study will forecast the evolution of the CO2 plume over time, by modeling the injected supercritical CO2 plume movement within the formations while honoring advanced trapping mechanisms such as CO2 trapping due to residual trapping, dissolution in saline water, and mineralization. Then, dynamic reservoir simulation models are fully coupled to 3D geomechanics models to study the impact of the injection on the well integrity, cap rock integrity as well as fault reactivation and integrity.3. Once the subsurface sites successfully pass the feasibility study, risk assessment, and mitigation, phase 3 is implemented to propose reasonable and economical surface facility configuration and pipelining scenarios that fit the subsurface sites’ requirements in terms of the number of wells and distance between them, depth of injection, required wellhead pressure, and proximity from CO2 source of emission.

the followed scientific approach resulted in concluding four feasible sites in the two fields to be deployed for a long-term and safe sequestration of more than 350,000 metric tons of CO2 per annum.

In this case study, we present the details of this integrated approach to account for the complex surface and subsurface nature of the western desert of Egypt during other CCS studies in similar environments.
Future Development Path of China's Fossil Energy under the Background of Carbon Peak and Carbon Neutrality
Authors: Jing Yu , Bo Zhou , Bing Li , Pingliang Fang , Hongyuan Zhang , Hongchun Huang , Changchang Chen
Published: February 2024

This research focuses on two main lines: national energy supply and demand security under the goals of carbon peak and carbon neutrality, as well as national energy green and low-carbon development. The research conducts quantitative prediction on the total demand and energy structure of national fossil energy under low-carbon transformation goals, providing reference for the country to implement green and low-carbon energy transformation and build a new energy system. Based on the national energy security and carbon peak and carbon neutrality strategic objectives, this study uses grey relational analysis to conduct multi-factor analysis and innovatively builds a fossil energy development potential prediction model under the "dual carbon" goal constraints. Three scenarios of robust-sustainable transformation, active-CCUS technology breakthrough, and radical-renewable energy technology breakthrough are designed to analyze the energy development paths under different scenarios, outlining the national energy development path and defining the quantitative targets for the fossil energy development phase. Through multiple model calculations, it is found that in the three scenarios, China's primary energy consumption will peak around 2030, with a peak value of approximately 5.99-6.01 billion tons of standard coal. The total energy consumption demand will slowly decline from 2030 to 2040, and maintain basic stability from 2040 to 2060. In the three scenarios of robust, positive and radical, China's energy consumption in 2030 is respectively 6.01, 5.99 and 6.01 billion tons of standard coal, of which non-fossil energy accounts for 24.9%, 27.0% and 28.3% respectively. By 2060, China's energy consumption will be approximately 5.63, 5.8, and 5.87 billion tons of standard coal, with non-fossil energy accounting for 73.6%, 80.0%, and 85.2% respectively. In response to the challenges facing the adjustment of the national energy supply and demand structure, this research has proposed corresponding development strategies from the three aspects of policy system, industrial layout, and technological innovation. The research results of this project have strong forward-looking, strategic and guiding significance, providing a theoretical basis for the country's energy transformation and development under the background of carbon peak and carbon neutrality, with significant comprehensive benefits.
Predicting Mud Weight Window from Well Logs by Integrating Deep Neural Networks and Physics Models
Authors: Phan Dung T. , Liu Chao , AlTammar Murtadha J. , Abousleiman Younane N.
Published: February 2024

The selection of an appropriate mud weight is important in drilling operations, as it plays a pivotal role in mitigating the potential for costly wellbore instability issues. The safe mud weight window is typically computed through analytical solutions that necessitate detailed rock properties as integral inputs. Conventionally, these rock properties are estimated based on well logs through empirical correlations. This paper introduces a wellbore stability analysis workflow that makes two changes to the conventional methodology. First, microporomechanics models are used to upscale the nano and micro properties of the mineral constituents to the macro rock properties. Unlike the correlation methods, this scientific approach can explain the origin of the rock properties. To help get the mineral composition data, a deep neural network (DNN) is trained on 15,979 data points to predict the volume fractions of silt inclusions, clay, and kerogen from gamma ray, resistivity, density, neutron porosity, and photoelectric logs. Second, another DNN is used in the workflow to speed-up the analytical solution for mud weight window computation. This DNN is trained to predict the mud weight window from in-situ stresses, pore pressure, well trajectory, and the rock properties. Its prediction is used as the starting point in the analytical wellbore stability solution to quickly determine the correct mud weight window. To demonstrate the practical application of this workflow, evaluations were conducted using a 480-foot shale well segment comprising 961 depth intervals. The results show that the hybrid approach can calculate 961 mud weight windows 5 times faster than the purely analytical solution.
Backup-Ring Optimization for High-Temperature and High-Pressure Applications Through Dynamic Composition Modification in Composite 3d Printing
Authors: Green J. T. , Rybak I. A. , Glaesman C.
Published: February 2024

Performance optimization was demonstrated in thermoplastic sealing systems for oil and gas equipment using emerging technologies in 3D printing to manufacture multicomponent composite structures. A custom 3D printer was equipped with a patented print head designed for dynamic mixing of individual feed materials and paired with advanced print-planning procedures to enable fabrication of novel thermoplastic structures. Simple flat backup rings used in O-ring sealing connections were manufactured with numerous architectures including homogeneous carbon fiber distributions, consistent with typical commercial processes and products, and novel carbon fiber distributions unique to this study. Specimens were tested in a sealing configuration to determine performance. Backup rings made from polyether ether ketone with uniformly distributed carbon fiber at high concentrations result in lower peak extrusion pressures than do unfilled grades but have the advantage of lower permanent deformation during long periods of steady-state loading. Flat backup rings were produced with discrete regions of each unfilled and carbon filled grades of polyether ether ketone and polylactic acid to optimize extrusion pressure at failure and long-term creep which were found to be dependent on both the volume ratio and orientation of the two regions relative to the primary O-ring seal. Uniform distributions of carbon fiber were outperformed by at least one binary or functionally graded architecture having the same nominal carbon fiber content. This demonstrates the viability of on-demand 3D printing of backup rings and provides a novel means of simplifying multicomponent systems while simultaneously expanding the operating envelope and life expectancy of oil and gas equipment since extrusion resistance and long-term creep in thermoplastic backup systems are major factors influencing service ratings for temperature, pressure, and service life. Innovative technology and methods described in this study enable fabrication of novel composite structures that increase performance when compared to homogeneous materials manufactured through traditional molding processes. In addition to supporting fabrication of sealing components for rapid response in oil and gas equipment, this technique provides a means of improving the overall performance of sealing systems without an increase to the size or complexity of the sealing assembly.
Yielded Zone Characterization While Drilling a Wellbore into Clastic Reservoirs Using Elastoplastic Modeling Approaches
Authors: Hamid Osman , Albahrani Hussain , Suaid Mohammed
Published: February 2024

Drilling a wellbore into a clastic reservoir exhibits complex rock behavior, including plastic deformation and yield zone development, which can affect wellbore stability and hydrocarbon production efficiency. Elastoplastic modeling methods have been increasingly used to simulate the drilling process and predict the location, shape, and size of yielded zones in the reservoir. This study aims to characterize the yielded zones in a sandstone reservoir during a borehole lifetime using elastoplastic modeling approaches. The methodology involves developing a finite element model of the sandstone reservoir using appropriate meshing techniques and boundary conditions definition for the problem. The constitutive model used in this study is the Drucker-Prager yielded criterion, which accounts for the non-linear behavior of the material during plastic deformation and yielding. The numerical method used is the finite element method, which discretizes the reservoir into small elements and solves for the stresses and strains in each element. The drilling process is simulated using incremental loading, miming the gradual application of drilling forces on the reservoir. The stress and strain fields in the reservoir were monitored during drilling, and areas of plastic deformation and yield were identified. The results showed that the elastoplastic modeling approaches used in this study accurately predicted the size, shape, and location of yielded zones in the clastic reservoir. The location and shape of the yielded zones agreed with the field observations.

Additionally, the model predicted the formation of a narrow, highly deformed zone around the wellbore, which is consistent with field observations. The size of the yielded zone depended on the drilling parameters, rock mechanical properties, and in-situ stresses. This study concludes that elastoplastic modeling approaches can be used to predict the size, shape, and location of yielded zones in sandstone reservoirs during wellbore drilling and production operations. The methodology used in this study can be used as a valuable tool for borehole planning and reservoir management. The innovation of this study lies within the use of elastoplastic modeling approaches to optimize drilling parameters and reduce the risk of wellbore instability in sandstone reservoirs. The results of this study can aid in designing drilling strategies that minimize the impact of yielded zones and improve wellbore stability, ultimately leading to increased production efficiency.
Predicting Reservoir Fluid Properties from Drill Cuttings: Application of GPC-UV Method for Reservoir Fluid Analysis
Authors: Yang Tao , Cely Alexandra , Moore Julian , Michael Eric
Published: February 2024

Drill cuttings are readily available for all wells we drill. Geochemical analysis has been employed to estimate key oil properties, such as API density and viscosity. However, most studies focus on drill cuttings with water-based mud. Identifying reservoir fluids in highly contaminated drill-cutting samples becomes a significant challenge when drilling wells with oil-based mud. Consequently, there is a high business demand for predicting reservoir fluid properties from drill cuttings with oil-based mud.

In 2015, Gel Permeation Chromatography (GPC) coupled with ultraviolet (UV) absorbance detection was introduced in the upstream industry. Elias and Gelin demonstrated the capability of the GPC-UV method to predict API gravity from drill-cutting samples with oil-based mud in unconventional reservoirs. This study extended the GPC-UV approach to conventional reservoirs across multiple fields from the Norwegian Continental Shelf and other global assets. We developed a multiple-wavelength method instead of fixed wavelength detection to explore correlations between GPC-UV detections and reservoir fluid properties.

The drill cuttings used in this study are from multiple fields from the Norwegian Continental Shelf and other global assets, where oil-based mud was consistently used for well drilling. Consequently, extracts from these cutting samples are contaminated by oil-based mud. Utilizing the GPC-UV method revealed clear oil peaks with the oil-based mud response appearing on the baseline. Correlating these results with GPC-UV data from stock tank oil samples and known reservoir fluid properties enables qualitative determination of fluid type (gas, oil, or water) and estimation of API from new drill cutting samples.

A digital solution based on machine learning, leveraging broad GPC-UV measurements, is needed to improve prediction accuracy further. While ongoing studies aim to establish a comprehensive database of GPC-UV measurements for stock tank oil and drill-cutting extracts, the GPC-UV method demonstrates impressive potential for analyzing reservoir fluids in challenging drill-cutting samples. Given the widespread availability of drill-cutting samples, this new method offers a cost-efficient and accurate means of determining reservoir fluid properties without resorting to downhole measurements or sampling. This method could fulfill the vision of considering "every piece of cutting as a PVT sample," with applications ranging from well placement and reservoir management to production optimization, flow assurance, and plug & abandonment.
Coupling Fluid Flow and Geomechanical Deformation Using AI & FEM Approaches
Authors: Hamid Osman , Almani Tameem , Alqannas Sulaiman , Alshanbari Ghalia
Published: February 2024

Coupling fluid flow and geomechanical deformation is a complex and challenging problem in geomechanics and reservoir engineering. The objective of this study is to develop a robust and accurate numerical model for coupling fluid flow and geomechanical deformation using machine learning (ML) and artificial intelligence (AI) techniques in combination with elastoplastic and finite element method (FEM) approaches.

The study involves developing an elastoplastic model to simulate the deformation of geologic materials under stress and incorporating fluid flow equations into the model using FEM techniques. The two simulators are coupled sequentially. During every sequential coupling step, the flow simulator sends pore pressures to the geomechanics simulator and receives back updated porosity and permeability values. The frequency of the coupling steps is problem-dependent and subject to further optimization and research. In addition, ML and AI techniques are used to reduce the frequency of the coupling steps, which can lead to substantial computational time savings given the fact that solving the geomechanical model numerically is a computationally intensive task. Furthermore, ML and IA techniques can also be used to optimize the input parameters, improve the accuracy of the model, and reduce overall runtime. The AI-based coupled model is tested against the traditional coupled model to validate the results.

The study demonstrates that coupling fluid flow and geomechanical deformation using ML and AI elastoplastic and FEM approaches is a promising area of research that can revolutionize our understanding of complex geological processes. The AI-based numerical model developed in this study provides an efficient and accurate tool for predicting the behavior of geologic materials under stress and can aid in developing more effective strategies for managing natural resources.

The use of ML and AI techniques in combination with elastoplastic and FEM approaches provides an innovative and efficient method for coupling fluid flow and geomechanical deformation. The AI-based numerical model developed in this study is a significant contribution to the field of geomechanics. It has potential applications in various industries, including oil and gas exploration, mining, and geothermal energy.
A New Approach for Reducing Sand Production During Water Breakthrough from Semi-Consolidated Sandstone
Authors: Alameen Mohammed B. , Almansour Abdullah , Elraies Khaled A. , Mohyaldinn Mysara
Published: February 2024

It is well recognized that most formations of semi-consolidated sandstone result in significant sand production during water breakthrough. In principle, the amount of sanding mainly depends on the rock strength and, subsequently, the reaction between the injected water and sand formation. Hence, this paper examines the sand (quartz) hydrolysis mechanism during water breakthrough to establish a correlation between silica dissolution and rock strength as a function of water saturation. Static and dynamic experimental approaches were used to correlate silica dissolution and rock strength as a function of water saturation. For the static method, pure quartz fine and coarse particles were utilized at different water compositions and temperatures to examine the reaction between the silica (quartz) and water. Then, selected cases were investigated further as a function of water saturation using a dynamic core flood test. The amount of silica reacted was monitored using a UV-Vis spectrophotometer, while the rock strength was investigated using uniaxial compressive strength. Semi-consolidated and consolidated sandstone core samples were employed for the dynamic tests. Based on the static experiment, the amount of sanding is significantly affected by the water quality (salinity) and pH. Results indicated that freshwater or distilled water has a higher impact on silica dissolution than brine water. Sodium chloride and Potassium chloride have the ultimate effect in silica dissolution in terms of hardness ions. In contrast, pH inconsistently impacts the silica dissolution, and an optimum pH value was selected. For the dynamic experiments, the results showed that an increase in water saturation leads to an increase in silica dissolution, which reduces the core strength. Sand production is, therefore, also a result of silica dissolution, which weakens the grain particles and connection at grain-to-grain contact. In conclusion, the water quality significantly impacts the amount of sand dissolved and the correlation between silica dissolution and rock strength as a function of water saturation was developed. The novelty of this paper is based on understanding the main reasons behind sand production for the semi-consolidated sandstone formation. The finding of this study is helpful in designing the optimum water quality used for water injection while reducing sand production issues.