bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anisotropic Rock-Physics Model and its Applications to Laminated Reservoirs Analysis
Authors: Vorobiev S. , Zharnikov T. , Vorobiev V. , Ayadiuno C. 
Published: February 2024

Abstract
The proposed anisotropy model allows to produce five independent dynamic elastic moduli for the veetrtical transverse isotropy (VTI) case. The VTI elastic moduli matrix can be rotated to match wellbore inclination or observed lamina dips to produce tilted transverse isotropy (TTI) anisotropy matrix with thirteen elastic moduli. The model is designed for the laminated shaly sands but is applicable for other cases of thin laminated reservoirs as well.
The model is based on the rock-physics model, which assumes that the anisotropy is caused by the lamination of clay and sands with a dispersed clay incorporated into sands’ matrix. Dispersed clay modeling is done using a combination of the Upper and Lower Hashin-Shtrikman and Reuss bounds. Laminated clay is incorporated using Backus averaging technique. VTI matrix can be rotated to the borehole frame using Euler rotation. Six plots and comparison of the independent laminated and dispersed clay volumes estimation technique has been developed for the model calibration.
The model has been tested on a number of wells from different regions. The model has applications in geomechanics for the elastic moduli anisotropy analysis as well as for the quantitative seismic interpretation (QI seismic). Thomsen weak anisotropy parameters can be computed from the VTI elastic moduli. The model provides new tool for the analysis of lamination and for petrophysical analysis of low resistivity low contrast (LRLC) sands. The model allows to calibrate clay volume in cases when X-ray diffraction (XRD) data is not available. It allows to produce two independent estimates of the dispersed and laminated clay volumes using Thomas-Stieber and shear moduli-based methods. The latter has been put forward in the process of the model development. These dispersed and laminated clay volumes’ estimates enhance LRLC saturation evaluation.
This paper provides novel dispersed and laminated clay rock-physics model. In addition, it proposes the model calibration technique based on six cross-plots and measured to modeled logs comparison. Additional validation of the model calibration correctness comes from two independent laminated and dispersed clay volumes estimates. The model provides new method of the total clay volume calibration. It opens new applications for the QI seismic inversion analysis in LRLC environments. All examples in this paper are based on the analysis of a gas bearing well located in offshore Australia. Thylacine-1 is the taken from public dataset exploration well (available in the Australian National Offshore Petroleum Information Management System https://nopims.dmp.wa.gov.au/Nopims/).
Identification and Characterization of Sonic Dual Arrival Events in High-Angle and Horizontal Wells for Enhanced Formation Evaluation and Well Placement
Authors: Bennett N. , Donald J. A. , Akinyose O. , Liu J. , Ma S. , Ghadiry S. , Abdallah W. 
Published: February 2024

Abstract
It is often assumed that reservoirs are homogenous in nature when conducting petrophysical evaluation of vertical pilot wells. However, this may not be the case with high-angle or horizontal (HAHZ) wells. Dual arrival events are well known to occur in sonic logs acquired in HAHZ wells where the compressional P-waves and shear S-waves propagate within the layer containing the tool sonde and refract along nearby shoulder beds. Here we present methods to process these dual arrival events to distinguish the tool layer slowness and provide a curtain section of formation slowness along the well track.
Physics modeling shows how the shoulder bed and tool layer arrivals present themselves to an acoustic receiver array as functions of measured depth, source-receiver offset, and nominal receiver azimuth. Built around a series of tau-P transforms in the common offset, common shot, and common ring gather domains, an automated time pick is presented. A labeling procedure then distinguishes between the tool layer and shoulder bed arrivals based on their apparent slowness and creates a log of tool layer P and S slowness. Finally, a ray tracing inversion is used to invert the arrival times associated with the shoulder bed arrivals for a locally two-layer model of formation P or S slowness.
Results of the physics modeling show that shoulder bed events have arrival times that vary with distance to the shoulder bed, have an apparent slowness that is faster than that of the tool layer arrival, and exhibit a sinusoidal moveout as a function of nominal receiver azimuth that indicates whether the shoulder bed is above or below the well track. The automated time pick is a generalization of the slowness time coherence workflow of Kimball and Marzetta. The ray tracing inversion determines the distance to and relative dip of the shoulder bed and distinguishes whether the shoulder bed arrival event is a reflection or refraction. The ray tracing inversion results are then woven together into a curtain plot section of formation slowness along the well track. This workflow of dual arrivals is demonstrated with both modeled waveforms and field data examples.
The above workflow produces logs of tool layer P and S slowness that are critical for accurate formation evaluation answers such as porosity, compressional and shear wave velocity ratio, and mechanical properties to derive stress estimates particularly when the well trajectory is close to a faster shoulder bed. Moreover, the resulting curtain plot section of P and S slowness is an acoustics analog of curtain plot sections of horizontal resistivity derived from logging-while-drilling electromagnetics measurements and so opens new avenues for increasing the use of acoustics for formation evaluation, completion operations, and well placement in HAHZ wells and geologically complex environments.
Modification of Shale Inhibition Properties using Novel Drilling Fluids with Gemini Surfactant and Associative Polymer as Additives
Authors: Ahmad H. M. , Javaid A. , Baig N. , Yasin S. , Iqbal T. 
Published: February 2024

Abstract
Drilling fluids are known as specialized fluids to modify rheology, filtration, fluid loss control, and shale inhibition properties for drilling applications in the oil and gas industry. Various additives are employed to change the properties based on the requirements of the drilling well and to meet the objectives of the drilling process. Additives such as polymers are used for rheology modifiers, fluid loss control modifiers, and shale inhibition control modifiers. Apart from polymers, a novel class of Gemini surfactants is also employed to modify the shale inhibition characteristics. In this work, a combined effect of polymer and Gemini surfactant was studied on the shale inhibition characteristics.
Various drilling fluid formulations were prepared by adding 0.25 to 0.4% concentration of associative polymer and 0.25% concentration of Gemini surfactant. All the drilling fluids were prepared based on the American Petroleum Institute standards. Two major tests were performed to investigate the effectiveness of prepared drilling formulations for shale inhibition properties. These tests include steady shear rheology and linear swelling tests in the presence of real samples of shale pallets.
The rheology of drilling fluids including polymer solutions and polymer surfactant solution was measured over a wide range of shear rates ranging from 0.1 (1/s) to 1000 (1/s). The shear stress and viscosity of the polymer solution increased by increasing the concentration of the polymer. However, the shear stress and viscosity of polymer solutions are slightly affected with the addition of surfactant solutions. It was observed that high-concentration polymer solutions were less likely by the surfactant solution. The linear swelling tests were performed with pure polymer and surfactant solutions along with the polymer-surfactant combined solution over a period of 48 hours. The linear swelling of shale pellets in the Presence of DI water was maximum while the swelling of shale pallets in the presence of polymer solution, surfactant solution, and polymer-surfactant solution was greatly reduced as compared to the swelling in DI water. The linear swelling of shale pallets in the polymer-surfactant solution (0.4%) - (0.25%) was approximately 107%.
The associative polymer and Gemini Surfactant have positive pendant groups and long alkyl chains in their structures. The positive pendant groups attach with the clay content in the shale while long alkyl chains encapsulate the shale minimizing the interaction of water with shale. Therefore, the synergistic effect of both polymer and Gemini surfactant improves the shale inhibition characteristics. This combination of associative polymer and Gemini Surfactant would be potential additives for drilling fluids to modify shale swelling and hydration inhibition characteristics.
Performance of Polyamidoamine-Enhanced Inhibitor in Mitigating Silicate Scale from Alkaline Surfactant Polymer (ASP) Flooding
Authors: Tan B. C. , Saaid I. M. , Mahat S. Q. , Razak A. A. A. , Bhaskoro P. T. , Anuar A. , Ahmed A. A. , Abubakar A. U. 
Published: February 2024

Abstract
Alkaline surfactant polymer (ASP) flooding is an effective chemical enhanced oil recovery technique to recover more hydrocarbon from maturing oilfields. However, the alkaline slug with high pH would dissolve quartz mineral in the sandstone formation which will result in silicate scaling issue. Silicate scales would precipitate in the formation near the production wellbore region, and further deposit inside production equipment and facilities. Consequently, the productivity of a well will be impeded. Scaling issues can be treated using chemical scale inhibitor (SI) through the application of squeeze treatment, continuous injection, or both. Many commercial SI available are not intended to mitigate silicate scale and these chemicals possess low biodegradability. Hence, more environment-friendly or "green" SI are being developed and tested for their effectiveness on scale inhibition. This paper aims to evaluate the performance of developed green silicate SI in mitigating silicate scale formation. The developed green silicate SI are composed of pteroyl-L-glutamic acid (PteGlu) that has enhanced with polyamidoamine dendrimers, either PAMAM-1.0 or PAMAM-2.0. Several experiments are conducted to assess the SI compatibility with synthetic brines, SI thermal stability, as well as SI effectiveness in treating silicate scale formation in static and dynamic conditions. Static adsorption test is also performed to determine the potential of developed green silicate SI for squeeze treatment. Results revealed that all tested SI are compatible with different synthetic brines. Among all, PAMAM-2.0-PteGlu SI yielded the best laboratory results at its optimum ratio of 1:333. It has the highest thermal stability as it experienced 34% weight loss at temperature 95°C. This SI also achieved 73.1% effectiveness in static scale inhibition test. From dynamic tube blocking experiment, it also managed to delay silicate scale precipitation by 48 times longer than the base case. Besides that, the adsorption capacity of PteGlu SI on crushed sandstone is also improved by approximately 60% with the addition of PAMAM-2.0. The green silicate SI developed in this paper could be utilized as environment-friendly alternatives in silicate scale control.
An Innovative Approach to Real-Time NMR Permeability Calibration Utilizing Azimuthally Oriented Formation Testing While Drilling
Authors: Fouda M. , Taher A. , Ramadan O. , Binghaith A. , Saad M. 
Published: February 2024

Abstract
Evaluating lateral variations of permeability is usually attempted using conventional logging tools and relying on field-specific porosity-permeability relationships. These transforms are generally built on core analysis and previous reservoir knowledge. Many Carbonate reservoirs given their complex pore structure, however, exhibit poor relationship between porosity & permeability and would hence need other more sophisticated methodologies and workflows to evaluate permeability. Nuclear magnetic resonance (NMR) is a well-known measurement that can provide indications of pore size in heterogeneous reservoirs and can hence be used for permeability evaluation. Formation testing while drilling (FTWD) can be used for mobility estimation while drilling. This paper presents the benefits of integrating logging-while-drilling (LWD) azimuthally oriented FTWD and NMR to reliably evaluate lateral permeability variations in horizontal wells.
NMR log-derived permeability is achieved by analyzing the T1 or T2 distributions and applying a cutoff differentiating pore size variation. The classification of the pore size distribution is input into established NMR permeability equations. These equations, however, have coefficients that need to be determined. The optimum irreducible water saturation cutoff as well as the permeability equation coefficients are ideally established with core analysis techniques. In horizontal wells across heterogeneous reservoirs having no representative core plugs formation testing can be used to help establish these parameters. Formation tester tools have been traditionally utilized to acquire a single pressure measurement and mobility calculation at any specified depth station. LWD testers, however, can be oriented around the wellbore to acquire several pressure and mobility values at different orientations. After investigating real time azimuthal images for bed boundaries and azimuthal variations, specific orientations of the formation tester can be selected to provide the most representative.
LWD NMR real-time permeability indicators showed pore size variations at the same porosity range. FTWD mobility data has enabled normalization of NMR permeability curves by providing calibration points at the test stations. The azimuthal orientation of FTWD tests was selected using LWD real time density and resistivity images to ensure the FTWD probe is not pointing to a tight bed boundary. High-resolution resistivity images from memory data provided an understanding to the mechanism causing variation in the azimuthal permeability profile. Combination of oriented FTWD and NMR permeability indicators aided real-time well-placement decisions and helped placing the wells into the most permeable zones. This paper presents an innovative approach for evaluating real-time permeability utilizing oriented LWD formation-testing mobility data with NMR permeability indicators.
Hydrocarbon Generation from Oil Shale Using Thermochemical Fluids: Integration of Geochemical, Petrophysical, and Core Flooding Methods
Authors: Aljurf S. S. , Elyasa A. , Hassan A. M. , El-Husseiny A. A. , Abu-Mahfouz I. S. , Mahmoud M. A. 
Published: February 2024

Abstract
The oil and gas industry has shifted its focus towards maximizing hydrocarbon production from unconventional reservoirs. Oil shale is an important unconventional resource that contains significant amounts of organic materials known as kerogen. This study aims to examine the effect of using thermochemical stimulation on fracture propagation and hydrocarbon generation from oil shale and characterize the rock sample using integrated geochemical and petrophysical methods before and after the stimulation process.
An integrated workflow to characterize the petrophysical and geochemical properties of oil shale was used before and after thermochemical stimulation. Laboratory measurements such as X-ray diffraction (XRD), X-ray fluorescence (XRF), Rock-Eval pyrolysis, and micro-CT were carried out to characterize the oil shale. The thermochemical stimulation was done using two chemical fluids, which are sodium nitrite (NaNO2) and ammonium chloride (NH4Cl). The coreflooding system was utilized to mimic reservoir conditions, where the fluids were injected separately and allowed to interact only upon reaching the core inlet. The sample was ultimately cleaned with methanol to remove the precipitated salts in order to be able to capture induced fractures effectively.
The stimulation of organic matter can lead to several alterations such as the enlargement of pore space and pre-existing fractures. The proposed workflow was successfully applied to the hydrocarbon generation from the oil shale sample. The TOC value declined after the stimulation due to the conversion of organic matter into hydrocarbons resulting from the thermochemical fluid reactions. Furthermore, the micro-CT images show that the pre-existing fractures were enlarged and formed a bath for new fracture networks. Along with this, the porosity of the sample increased due to the generation of new fractures. The more fluid cycles there are, the more efficient it is to convert organic matter into hydrocarbons. Also, the characteristics of the sample itself can affect the results of the reaction; thus, the higher the silica content, the more challenging the reaction. The XRD results after stimulation show that the calcite percentage decreased from (37.6%) to (19.2%) and quartz from (60.5%) to (48.1%), suggesting dissolution driven by the acidic thermochemical fluids.
Overall, this study introduces a new technique that can be utilized to stimulate and generate hydrocarbons in situ from oil shale source rocks. Oil shale is not exploited properly due to the complex nature of organic matter. So, the suggested workflow can pave the way to introducing a downhole technique to stimulate and produce these resources more effectively.
Federated Learning for Seismic Data Denoising: Privacy-Preserving Paradigm
Authors: Guruprasad Kamalesh Kumar Mandakolathur , Ambulkar Gayatri Sunil , Nair Geetha 
Published: February 2024

Summary
Federated Learning (FL) is a framework that empowers multiple clients to develop robust machine learning (ML) algorithms while safeguarding data privacy and security. This paper's primary goal is to investigate the capability of the FL framework in preserving privacy and to assess its efficacy for clients operating within the oil and gas industry. To demonstrate the practicality of this framework, we apply it to seismic denoising use cases incorporating data from clients with IID (independent & and identically distributed) and Non-IID (non-independent and non-identically distributed) or domain-shifted data distributions. The FL setup is implemented using the well-established Flower framework.
The experiment involves injecting noise into 3D seismic data and subsequently employing various ML algorithms to eliminate this noise. All experiments were conducted using both IID and Non-IID data, employing both traditional and FL approaches, various tests considering different types of noise, noise factors, number of 2D seismic slices, diverse models, number of clients, and aggregations strategies.
We tested different model aggregation strategies, such as FedAvg, FedProx, and Fedcyclic, alongside client selection strategies that consider model divergence, convergence trend similarity, and client weight analysis to improve the aggregation process. We also incorporated batch normalization into the network architecture to reduce data discrepancies among clients. The denoising process was evaluated using metrics like mean-square-error (MSE), signal-to-noise ratio (SNR), and peak signal-to-noise ratio (PSNR).
A comparison between conventional methods and FL demonstrated that FL exhibited a reduced error rate, especially when dealing with larger datasets. Furthermore, FL harnessed the power of parallel computing, resulting in a notable 30% increase in processing speed, enhanced resource utilization, and a remarkable 99% reduction in communication costs. To sum it up, this study underscores the potential of FL in the context of seismic denoising, safeguarding data privacy, and enhancing overall performance. We addressed the associated challenges by experimenting with various approaches for client selection and aggregation within a privacy-preserving framework. Notably, among these aggregation strategies, FedCyclic stands out as it offers faster convergence, achieving performance levels comparable to FedAvg and FedProx with fewer training iterations.
Wellbore and Caprock Integrity During CO2 Injection in Saline Aquifer
Authors: Han Y. , Liu H. H. , Alruwaili K. , Altammar M. J. 
Published: February 2024

AbstractDeep geological formations, such as saline aquifers, unmineable coal seams, and depleted hydrocarbon reservoirs, offer a great potential for large-scale underground storage of carbon dioxide (CO2). Well injectivity, formation storage capacity, wellbore integrity and caprock integrity are among critical topics in CO2 underground storage. This work focuses on constraints imposed by the wellbore stability and caprock integrity on the wellbore injectivity. The buildup of bottom hole pressure, the evolution of CO2 plume, and the distribution and evolution of pore pressure in the geological formation are predicted using semi-analytical solutions. The disintegration risk of wellbore is assessed with updated bottom hole pressures at various injection times. The caprock integrity is evaluated by applying the evolving vertical total stress in the saline aquifer in contact with the caprock at the bottom of caprock layer to assess the risk of fracturing in caprock.
Application of Autonomous Real-Time Digital Twin for Structural Health Monitoring and Integrity Assessment of Damaged Fixed Offshore Structures
Authors: Shahir M. L. , Shawn E. L. , Wong B. S. , Ann L. L. , Ellis W. S. K. , Belden C. C. Y. , Michelle H. C. W. , Mekan S. N. , Anas K. A. A. , Sarah B. S. , Ickx K. B. 
Published: February 2024

Abstract
The objective of this study was to deploy an autonomous real-time Digital Twin (DT) Structural Health Monitoring (SHM) system on offshore platform to enable continuous real-time monitoring and automated evaluation of the structural integrity based on the offshore feeding data of a 4-legged fixed substructure which has experienced vessel collision earlier. The collaboration between asset owners, asset operators, and academic researchers aimed to develop an advanced DT SHM system for this purpose.
The SHM system implemented a comprehensive framework that integrated software and hardware components with Internet of Things (IoT) capabilities. The hardware facilitated the collection of raw data, while a proprietary physics engine was developed to enable autonomous structural analysis for calibration and subsequent integrity assessment to identify the most probable source of structural anomalies. Real-time data acquired online were used to derive useful structural engineering parameters, forming a digital twin that emulated the actual offshore condition of the structure.
The deployment of the autonomous SHM system provided asset operators with valuable insights into the structural performance of the substructure in real-time. This enabled fast decision-making aiming to improve the efficiency of engineering manhours as well as optimisation of inspection and maintenance practices. The system outperformed conventional methods by timely quantifying the influence of assessed damages on the global substructural integrity, allowing for more accurate benchmarking and up-to-date information.
This case study emphasizes the significance of adopting autonomous Digital Twin SHM systems for offshore structures, particularly when compared to manual assessments. The implementation of the autonomous system reduces both time and effort while providing reliable benchmarking and up-to-date information on the structural integrity of the monitored structure. This highlights the importance of utilizing advanced SHM technologies to optimise the inspection and maintenance practices of offshore structures.
The objective of this paper is to present the framework for a Digital Twin SHM system that is designed for real-time global structural monitoring.