bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of Pore Structure and Fluid Saturation of Organic-Rich Rocks Using the Set of Advanced Laboratory Methods
Authors: Mukhametdinova A. , Andreyev B. , Latypova M. , Kalmykov G. , Kalmykov A. , Bogdanovich N. , Spasennykh M. , Cheremisin A. 
Published: October 2023

The global shift in energy reserves structure, including Russia, is moving towards the effective development of unconventional oil and gas reservoirs (EIA 2013). However, the problem of assessing hard-to-recover reserves in low-permeability, organic-rich reservoirs still lacks a comprehensive solution. This is primarily due to the lithological, physicochemical, and reservoir properties of the rocks, and often results from the utilization of a limited set of laboratory techniques that yield different values for the same measured property. Several studies on various aspects of unconventional reservoirs also emphasize the necessity of employing alternative techniques for laboratory analysis of core samples (Handwerger et al. 2012; Yuan et al. 2019; Curtis et al. 2012).
Currently, the depletion of oil and gas reserves in traditional sandy reservoirs has made the search for new hydrocarbon deposits increasingly important. A significant area of focus in this regard is the study of potentially productive intervals within unpromising kerogen-clay-siliceous strata that are rich in organic content. One notable example of such intervals is the high-carbon Bazhenov formation in West Siberia (Ulmishek et al. 2003; Kontorovich et al. 1997). Modern field development methods, such as hydraulic fracturing (HF), the use of organic solvents, and thermal recovery, have enabled increased production from high-carbon formations with low reservoir properties. However, in order to make accurate predictions for the development of high-carbon formations using modern methods, it is crucial to accurately describe the complex void space system and understand the relationship between hydrocarbon compounds, water, and the solid rock matrix. Otherwise, it is impossible to predict the behavior of the void space following anthropogenic interventions using modern field development techniques.
To date, several methodological recommendations and approaches have been developed for assessing oil resources and calculating reserves in Bazhenov formation deposits (Bilibin et al. 2015; Petersilye, Komar, et al. 2016; Prishchepa et al. 2015). However, these methodological recommendations should be carefully adjusted depending on the type of formation, the degree of organic matter (OM) transformation in high-carbon formations, and other factors. Factors such as macro- and microlithological characteristics of the section, mineral composition, reservoir properties, type, maturity, and amount of OM in the rock, morphology of the pore space and its hydrocarbon (HC) filling, the presence of free and bound water, and wettability, among others, should be initially included in the fluid dynamic model. These factors form the basis for refining existing methodological recommendations.
The Wiggle that Makes a Difference: Using AI to get the Right Wavelet with Multi Well Input
Authors: Alkhanjari H. S. N. , Glukstad M. M. , Alqassabi S. H. , Alrubaiey A. , Ali N. , Albadi O. A. 
Published: October 2023

Abstract
A common problem when carrying out seismic interpretation in the Two-Way travel Time (TWT) domain is to choose the adequate wavelet when performing well to seismic tie. This step is also crucial in any Quantitative Seismic Interpretation (QI) project where the use of the right wavelet makes a big difference. Many of the fields in Oman have several wells with the appropriate data, i.e., Time-Depth (T-Z) pairs or Check shot data (VSP) and Sonic, but the quality of the log data and the short extend of the Sonic log requires calibration, making it very challenging to select the right well for the analysis. The interpreter often looks at several wells, in the same field, but with different data and quality. Although multi-well to seismic tie is available in most commercial software, the problem of dealing with variable data quality, having to select the right wavelet, that will make sense for all the wells, is still a problem that is very time consuming and often difficult to resolve. The interpreter has to make a decision but lacks any proper quantitative or qualitative approach on which to base the choice of wavelet. Recently an Artificial Intelligence (AI) tool was released, Automated Seismic to Well Tie (AWT) in Petrel version 2021, which uses the seismic volume and well data to obtain the best wavelet which provides the best tie when generating the synthetic seismogram, with minimum effort, in matters of few hours. The tool looks at all the possible wavelets and defines the best match and ranks the outcome for the different wells. Crucial part of this methodology is to provide the computer with as clean as possible data set. The team tested this tool in field XX and with technical support from the software owners, obtained spectacular results in a very short time saving weeks of work.
Keep Your BHA Cooler While Drilling Through High-Temperature Formations
Authors: Alabdulmohsen Zainab , Al-Shubaith Abdullah , Anioke Chidiebere , Al-Saqer Qassem 
Published: October 2023

Abstract
Typically, drilling fluids exhibit lower rheological properties at elevated wellbore temperatures, which affect wellbore cleaning capabilities, filter cake stability, down-hole tools lifetime, and increase the possibility of stuck pipe events. Drilling through high temperature formations &gt;300°F using oil-based drilling fluids often requires the use of mud coolers to help maintaining BHA tools and to reduce any risk of failures that can lead to high associated costs of non-productive time (NPT).
To overcome the above associated challenges, field experience introduces a flexible engineered approach. This approach is based on a lubricant that is an environmentally acceptable and as polymeric fatty acid solution for oil-based muds (OBM). From an operational standpoint, this solution induces a cooling effect of the mud hundreds of feet ahead without the need of circulating it or using a mud cooler. This lubricant worked to reduce the frictional effect resulting in temperature reduction while drilling and maintaining uniform rheological property of the drilling fluids. Also, a laboratory work was conducted using a metal-to-metal approach to approve the lubricity effectiveness of this solution in friction reduction.
An addition of 1-2% of the proposed lubricant to OBM system resulted in a drop in temperature by ~10°F. This paper aims to present the effect of drilling high-temperature wells &gt;300°F which can lead to high potential of having failure in the measuring-while-drilling (MWD) system due to the equipment limitations. Furthermore, it shows how this lubricant solution could reduce circulation time to 50% per 1,000 feet and cool down MWD temperatures with torque reduction up to 6% compared to previous operations. Laboratory work also proved that this solution could provide friction reduction up to 23%.
This friction reduction provides lower downhole temperature profiles by adding OBM lubricant while drilling and has significantly assist in minimizing NPT, the probability of MWD failures, and insure a smooth operation.
Predicting Porosity from Drilling Data Using Machine Learning – Challenges and Solutions
Authors: Alhowaish H. A. , Mezghani M. M. , Shakriov A. 
Published: October 2023

Abstract
Porosity is key to understanding reservoir potential for hydrocarbons. The main methods of acquiring porosity data are through wireline logging or detailed laboratory measurements. Although informative, these operations are restricted by their economic and operational costs. Machine learning (ML) is a branch of artificial intelligence that uses input data to train a model and generate a prediction, saving cost and time. The objective of this paper is to predict well porosity with high accuracy and reliability with machine learning, using only drilling data.
This study utilizes a supervised ML method with a gradient boosting algorithm. Out of 10 wells, 9 are used for training which is split into a 9 to 1 ratio of training to testing, and another well for validation. The input parameters shown at each depth are conventional drilling parameters, such as weight on bit, revolutions per minute (RPM), torque, etc. Input parameters are preprocessed prior to filtering and clustering to enhance the model quality. The model performance is measured using root mean square error (RMSE) and mean average error (MAE). The model is then assessed using the validation well with the same metrics as the model performance.
The model training showed promising results in predicting porosity with the ML methodology. After preprocessing and parsing the data, clustering analysis is done to group data points based on their similarity. A permutation feature importance analysis revealed the input variables that contributed most to the outputs, mainly RPM and torque. The model's performance was also enhanced by modifying uncertain intervals in the input parameters to remove outliers and give a lower RMSE and MAE. We then investigated the difference between a model predicting porosity for a specific geological formation against a global ML model. A formation-based model takes input data from a single formation to predict porosity, while a global model takes input data from all formations to make a prediction at any point. Results show that a formation-based model is highly sensitive to the input data and number of wells compared to a global model. Next, we plan to improve the preprocessing techniques, include a sensitivity analysis, and evaluate the two models further.
Previous studies have highlighted the need to predict porosity at a more economically viable approach. But few have solely used surface drilling parameters in machine learning, which is extensively monitored at every borehole and can simplify ML models without reducing performance. This study demonstrates the effectiveness of using only drilling data in predicting porosity, proving beneficial to reservoir characterization and hydrocarbon exploration.
Gas Compositional Effect on Fit-For-Purpose CO2 Storage Capacity Estimation: A Case Study in Malaysian Depleted Clastic Gas Reservoir
Authors: Affandi R. A. , Yakup H. , Hendraningat L. , Jalil M. A. , Tewari R. D. 
Published: October 2023

Abstract
Amidst growing concerns about global warming and climate change, there has been increasing attention given to the storage of CO2 using underground geological structures. Depleted gas reservoirs have been identified as one of the most promising geological solutions for CO2 storage, owing to their data accessibility, economic feasibility, and safety. Currently, extensive studies are being conducted to appraise the CO2 storage potential of offshore Malaysian Depleted Clastic Gas Reservoir. The aim of this paper is to examine the impact of gas properties on CO2 storage capacity estimation in depleted gas reservoirs. The scope of the study includes a numerical simulation (Dynamic CO2 storage capacity) approach to model the behaviour of CO2 in the subsurface and to assess the significance of gas properties on the storage capacity of the reservoir. The Material Balance analysis (MBAL) method is employed in this study to model the potential CO2 storage capacity in the subsurface, taking into account the impact of gas properties such as z-factor and Gas Formation Volume Factor (Bg). The simulation process starts with history matching the historical data by using improved workflow. It eventually continued to forecast the production and CO2 storage capacity.
Gas properties, in particular z-factor and Bg, significantly impact CO2 storage capacity estimation in depleted gas reservoirs, mainly due to the dynamic of injected CO2 composition which is mixed with residual gas. The study observed that a gas properties difference (Bg at Pinit is from 0.0109 to 0.0122 ft3/scf) in the reservoir D resulted in a 15% difference in CO2 storage capacity, while for the reservoir I case, a difference in gas properties (Bg at Pinit of 0.00840 to 0.00894 ft3/scf) resulted in a 3% difference. Besides that, an improved technique for estimating fit-for-purpose CO2 storage capacity was established in this study by generating and assigning individual PVT models through flash and recombination processes for reservoir without sufficient PVT information. The models are matched to the initial saturation pressure using characterized fluid properties available in major reservoirs, resulting in a more accurate and effective estimation of CO2 storage capacity. The study concludes that, when using the Material Balance analysis method, gas properties must be considered and properly characterized for better understanding and accuracy of CO2 storage capacity estimation. This paper provides new insights into the role of gas properties (z-factor and Bg) in CO2 storage capacity estimation. In addition, this work has improved the workflow for fit-for-purpose CO2 storage capacity estimation using Material Balance analysis. The results of this study provide a fresh perspective on the optimization of fit-for-purpose CO2 storage capacity estimation.
New Form of Skin Due to Flow Convergence Towards Perforation Intervals in Hydraulically Fractured Wells. Is Perforation a Concern Post Fracturing?
Authors: Samy A. 
Published: October 2023

Abstract
Total skin includes different components which may contribute to the additional pressure drop around wellbore due to formation damage, perforation, partial penetration, well deviation, two phase flow, stimulation (or fracturing) and non-Darcy flow. Even though successful frac jobs usually yield incremental production gains, there are other skin components which can cause positive skin and reduce the potential (ideal) incremental gain post-fracturing such as fracture face skin and choke skin in horizontal wells with transverse fractures. There is a common understanding that perforation is important for frac execution only but not a concern during production post-fracturing because well productivity will be dominated by fracture conductivity. However, this paper shows other form of skin which can impact well productivity post-fracturing due to flow convergence inside fracture towards perforation intervals.
The method is to calculate the additional pressure drop and the associated skin due to radial flow convergence inside fracture towards the perforation holes. The method considered the effective flow area which is in communication with fracture wings, and it depends on perforation density, effective entrance hole and gun phasing. The procedures include modification to the flow equation which describes choke skin due to well orientation in transverse fractured wells.
This paper shows that perforation is a concern and can impact well productivity post-fracturing especially in moderate to high permeability formations. This skin component should be considered in estimating flow rate post fracturing in order to avoid over-estimation of well productivity. Also, it discusses the importance of adding perforation intervals post-fracturing to enhance well productivity and the optimum conditions / circumstances that requires adding perforation post-fracturing.
This paper presents a new form of skin which should be considered during well design and frac design. By avoiding this skin, well productivity post fracturing can be significantly increased.
Numerical Simulation of Proppant Heterogeneous Distribution in Shale Gas Reservoirs
Authors: Hou Tengfei , Zhang Yang , Shang Litao , Zhang Shiling , Xiao Fengchao , Bai Haoli , Sun Xun , Qiao Yan , Xu Gang , Zhang Qingyao 
Published: October 2023

Abstract
Slickwater fracturing with high injection rate and large volume has been widely used in the development of shale reservoirs, while the proppants cannot distribute uniformly in fracture networks, usually in the forms of sand-bed, separated pillars and local displacement. Thus, there are still some key issues need to be figured out for better fracturing design, such as the proppant placement status in complex fractures, and how to achieve effectively propped fractures, etc.
In this paper, a three-dimensional proppant transport model is established by Dense Discrete Phase Model (DDPM). The flow field and concentration distribution of the proppants were analyzed, by tracking the trajectory of proppants in different types of complex fractures. Besides, the placement status of particles in the primary and secondary fractures was analyzed. In addition, we also conducted the research on proppant transportations in perf clusters. Finally, according to actual fracturing treatment schedule, three different sizes of proppants were gradually injected and the distribution law of the proppants was studied.
Based on the concentration distribution of proppants in the complex fractures, fractures can be divided into four zones: pure fluid zone, critical suspension zone, flowing slurry zone and settling bed zone, while the critical suspension zone and flowing slurry zone of secondary fracture are smaller than primary fracture. Besides, the proppants concentration entering into the fractures far from the entrance is more than that entering the fractures near the entrance. The ratio of proppant concentration into each perf cluster (3 clusters per stage) is about 1:1.5:2, while that concentration ratio is 1:1.25:1.6:2 in four clusters per stage scenario, while the proppant concentration is inversely proportional to the amount of proppant and liquid injected. The proppants of 100 mesh injected in the early stage migrates to the far end of the fracture, and some enters into the branch fractures, while most of them settled in the sand bed of the main fracture. Meanwhile, the following 40/70 mesh proppant injected is mainly distributed in the main fracture at flowing slurry zone. The 30/50 mesh proppant injected in the later stage is mostly located at the fracture entrance and at the top of the sand bed. Finally, it was found that high injection rate, small particle size, and low-density proppant could improve proppants preferentially entering branch fractures.
This paper provides a clear insight of proppant distribution law in complex fractures under field fracturing treatment schedule. And our model can be used to optimize the fracturing treatment design.
Valve Leakage - How Acoustic Emission and Artificial Intelligence Can Reduce Losses and Increase Safety and Efficiency in Oil and Gas Plants
Authors: Hettegger Michael , Berezovsky David 
Published: October 2023

Abstract
The paper provides an overview of the current challenges of valve inspection in the industry and how they can be overcome with the help of software and artificial intelligence. Studies show that 5-10% of valves in oil and gas plants are suffering from internal leakage which can lead to economic losses, health and safety issues or potentially to environmental pollution. Acoustic emission testing is a relatively modern but already well-established technology for leak detection in valves, however existing solutions show some limitations. These are among others e.g., their complexity of use, they need trained and experienced personnel, the time required to perform analyses and the use of solely proprietary and closed devices. Interviews with experts performing inspections in the field have shown that they are facing challenges such as using the right measuring points, finding the right duration of measurement, applying the right pressure when placing the sensor and finally transferring data and interpreting the results. Research has shown that interpretation of results depends very much on experts' know-how (Singh, Saleh Al Kazzaz, 2003) and reproducible results have thus been difficult to achieve. This causes the difficulty for companies to use the data for further purposes, such as predictive maintenance.
To address this problem, over 2000 measurements in laboratories and simulated leakages in the field have been collected, taking into account different media/pressures/different valve sizes/nominal diameters and valve types. The experience gained and the data collected were used to build a smart and mobile inspection system which is able to standardize inspection processes for leak detection in valves. It was built on the well-established acoustic emission technology, extended with digital features.
Our digital approach has proven that a standardized process is able to significantly reduce the dependence on expert knowhow. By combining AE signals with state-of-the-art signal processing, algorithms and machine learning models, the vast amount of AE signals can be processed within seconds, providing reliable results even in noisy environments. These developments provide companies a new opportunity for in-house valve inspection, a possibility to fight against shortage of skilled labour and increase the reliability of their assets.
Remedial Alcoholic Condensate Banking Treatment in Deep Gas Wells in the Sultanate of Oman
Authors: Al Aamri Ghusun , Al Yaaribi Ahmed , Al Hinai Adnan 
Published: October 2023

Abstract
One of the most gas production challenges from tight gas reservoirs in the sultanate of Oman is condensate banking. Such a phenomenon usually results in sharp declines in gas and condensate production after reaching the dew point, and becomes more influential in the unconventional and depleted condensate-gas fields. Another challenging aspect is the complex and expensive post-drilling and post-fracturing cleanout due to the high capillary pressures slowing the completion brine flowback. Successful field applications developed with alcohol treatments in deep tight sandstone gas wells have minimized the impact of condensate banking on production in the Sultanate of Oman.
Thorough lab testing and screening processes to optimize the formulation of the treatment and maximize the chances of success were conducted prior to taking the application to field implementation. In particular, the solvent type and concentration were selected carefully to avoid any precipitation issues that might arise from incompatibility between the alcohol treatments and the highly saline formation water. In addition, careful HSE planning was required before the field deployment due to the low flash point associated with such treatments.
A campaign of 4 field trials was conducted on several gas wells that are impacted by condensate banking. For the condensate banking, the treatments managed to restore the gas production from closed-in wells while increasing the condensate rate by more than 170% and gas rate by more than 220%. These promising results have resulted in planning a wider deployment scope to further test the operational limits of the alcohol treatments and optimize the production from several fields that are impacted by condensate-blockage impairment.
Using this alcohol treatment as an alternate to traditional water and condensate blockage remediation has improved efficiencies in time, production and materials. The application provides a more economical means to enhance production in tight gas fields of the Sultanate of Oman.