bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pre-Drilling Pore Pressure Prediction Technique Based on High-Quality OBN Seismic Velocity and its Application in K Oilfield
Authors: Xin Chen , Khdhaouria Mourad , Rouis Lamia , Huang Qingfeng , Xiaolin Lv , Min Zhao , Xiaoliang Li , Dengyi Xiao , Qunli Qi , Wenwen Yu , Qiang Liu , Xin Hu , Kongzhi Huang 
Published: May 2024

Abstract
Pre-drilling pore pressure prediction based on seismic velocity is a critical step in the oil and gas industry to ensure drilling safety and optimize well construction. However, due to the limit resolution of the seismic data, the pore pressure prediction result is not good enough for well drilling. With the increasing quality of new seismic data, this study proposed a new pre-drilling pore pressure prediction technique based on the high quality OBN seismic velocity.
This new technique consists 6 steps: ①Abnormal high pore pressure identification based on the pore pressure test, mud weight, well logging velocity and seismic velocity. ②Mechanism analysis based on the lithology, sequence stratigraphic and tectonic movement. ③Feasibility analysis based on the comparing the OBN seismic velocity with abnormal high-pressure interval. ④Geological consistency OBN seismic velocity optimization, based on high-quality logging velocity. ⑤Pore pressure prediction based on the petrophysical analysis and pressure prediction parameters optimization.
This new technique has been successfully applied in the K oilfield in Central Asia. Integrated pressure testing data, mud weight, and seismic velocity can clearly identify high pore pressure in middle to deep formation of the study area. The abnormal pressure is formed due to under-compaction, where the mudstone of the maximum flooding surface acts as a barrier to the outflow of pore fluids in the deep layers, resulting in abnormally high pore pressure. Abnormally high pressure can be clearly identified by the OBN seismic velocity spectrum, with different pressure gradient intervals having different OBN seismic velocity gradients. Geological consistency velocity optimization methods can enhance the accuracy of OBN seismic velocity interpretation and more matched with well log velocity, thereby improving pressure prediction accuracy. Modified Fillippone method was used for pore pressure prediction, and more accurate Vmax and Vmin can be obtained through rock physics analysis, further enhancing pressure prediction accuracy. From the initial seismic velocity spectrum and pressure test results from nearby drilled wells QC, the results were matched with pore pressure prediction results, with a high correlation (up to 92%).
The new pre-drilling pore pressure technique integrated the advantages of pore pressure testing, high resolution of well log velocity, and high-quality of OBN seismic velocity. It enhances the accuracy of OBN seismic velocities through geological consistency seismic velocity optimization and improves the accuracy of pressure prediction parameters (Vmax and Vmin) through rock physics analysis, and ultimately improving the accuracy of pore pressure prediction. This method is applicable to both clastic layers and carbonate layers.
Direct Hydrocarbon Saturation So from Core Plug and Well Cuttings Using Geochemistry Based Method of Extraction-A Cost Optimized Alternative Method for Optimal Test Zone Selection and STOIIP Calculation
Authors: Koksalan T. , Alwahedi M. A. A. , Ghosh D. , Ahsan S. A. 
Published: May 2024

Abstract
We can assess reservoir saturation with high confidence and make timely and cost effective decisions about testing and perforation by measuring hydrocarbon directly on core and cuttings extracts and doing SARA (Saturate, Aromatic, Resin and Asphaltene) compositional analysis integrated with mud log and petrophysical data. Conventional reservoirs usually measure hydrocarbon saturation with petrophysical interpretations based on well log data. But petrophysical methods are often based on resistivity, which is indirect, interpretive and can give unreliable water saturation (Sw) in carbonate reservoirs with complex porosity and different fluid distribution. We have seen that, in many cases, Sw is underestimated, and this causes significant variation in the amount of hydrocarbon in place. Also, the Sw is calibrated by lab measurement of water extracted from core plugs with Dean Stark method. But Dean Stark method can also give misleading Sw, especially when water bound water exists. The aim of this study was to measure oil saturation directly by extracting oil from core plugs. This method has been shown to agree very well with the test results and has potential to provide a more reliable STOIIP and choice of best testing intervals.
A suite of more than two hundred (200) core plug samples from different wells were analyzed. Total Extract Yield was determined on extracted samples to assess hydrocarbon saturation through the reservoir of interest. Our method is based on extraction of pulverized core plugs and well cuttings samples. The extracted oil is collected in glass vials, measured in milligrams and is reported per gram of the rock weight extracted. The weight of the oil extracted is then converted, using a mathematical expression, into water saturation (Sw).
The approach presented here utilizing extract yield normalized to rock weight has been adopted to assess hydrocarbon saturation. Furthermore, the use of Sw obtained and calculated from extract yield of cores, coupled with conventional open hole logs and mud log, core samples can assist in making time-sensitive drilling and completion decisions, such as selecting optimal perforation zones and identifying high water saturation zones for plugging. Additionally, it can help in keeping horizontal wells within sweet spots and in estimating in-place hydrocarbon volumes in both conventional and unconventional reservoirs. Perforation interval selection or isolation of high-water zone in a horizontal well scenario is particularly very critical in thin and tight reservoirs where improper well completion may severely impact reservoir performance and project’s economics.
Next Chapter of Drilling is Opened by Using New Technologies to Reduce Shocks and Vibrations and Improve Drilling Performance
Authors: Al-Meer Ali , Fakhrylgayanov Ayrat , Gari Abdulrahman , Alqahtani Khalid , Osman Ahmed , Alabdallah Mansour , Santoso Gagok , Franco Nata , Almomen Mohammed , Aswal Uttam 
Published: May 2024

Abstract
In the oil and gas industry, one of the biggest challenges in drilling deep gas wells is to maintain the drilling tools in good working condition despite the harsh drilling environment, which can cause shocks and vibrations. This is especially true in long horizontal sections with reservoirs that have heterogeneous formations such as tight and interbedded porous limestone formations between anhydrite layers. During drilling operations, severe stick-slip, shocks, and vibration can occur. Furthermore, high-frequency torsional oscillations (HFTO) can be generated, reducing the rate of penetration and damaging drilling tools or bits. This affects the drilling performance and efficiency.
A new technology of HFTO dampener tools was used in a Lump SumTurnkey (LSTK) gas project in the Middle East. By applying certain optimized drilling parameters, significant improvements were made in drilling performance. The longest footage was drilled with more than 4,450 ft in a single run, achieving a total measured depth of 19,800 ft. The new technology reduced vibrations amplitude by 50% and enabled drilling in highly challenging long-lateral sections more efficiently. These results played a crucial role in achieving the well objectives with a huge increase in drilling performance and efficiency. The technology also allowed for proper identification of optimum drilling parameters in the reservoir.
This paper describes the field deployment of the HFTO dampener tool and the application of optimized drilling parameters, which were used for the first time to drill the challenging horizontal lateral section in the LSTK gas project. The results can be implemented in any project worldwide.
A Gupco Drilling Case Study Illustrates How Shifting an Organization’s Culture Can Shape How it Approaches Innovation
Authors: Saloma Mohamed Farouk , Salama Ayman , Ibrahim Lotfi , Elsayed Mohamed Farouk 
Published: May 2024

Abstract
Change the collective organizational culture from risk avoidance to risk taking because of the realization that taking calculated risks can lead to innovation and progress. This approach enabled a more agile and adaptable response to enhance performance while also cultivating a culture of continuous improvement.
To achieve the required change, a communication and engagement strategy was selected through the following.
To help GUPCO drilling organization understand the need for change, a high-value learning study was carried out. The study involved analyzing current practices, identifying areas of inefficiency, and exploring innovative approaches to enhance productivity and performance. To help GUPCO drilling organization start making the necessary adjustments, a workshop on drilling performance improvement was held. The workshop aimed to identify areas of improvement and develop strategies to enhance drilling performance. It provided a platform for employees to share their insights and collaborate on implementing effective solutions.
By adopting this mindset, the GUPCO drilling team was able to approach challenges with a fresh perspective, encouraging innovative solutions and fostering a culture of continuous improvement. Consequently, the drilling team unlocked previously inaccessible opportunities. This new working philosophy was implemented in the EDFU field 2021 campaign by combining two sections that had never been drilled together. This resulted in time and cost savings and the unlocking of opportunities that had been blocked since 2017. Same approach of combining two sections was utilized in Saqqara, July, and October fields with outstanding results. The successful implementation of this new working philosophy not only allowed the drilling team to tap into previously untapped opportunities but also led to a significant increase in productivity and overall success, solidifying the effectiveness of this strategy and paving the way for future attempts.
By fostering a culture that values experimentation, risk-taking, and open communication, companies can create an environment where employees feel empowered to think creatively and explore new ideas. This cultural shift can lead to increased collaboration, the breaking down of silos, and a greater emphasis on continuous learning and improvement, ultimately driving innovation forward.
Research on the Influence and Mechanism of Particle Geometry and Mechanics on the Strength of Temporary Plugging Zone
Authors: Zhao Feng , Guo Jianchun , Ren Jichuan 
Published: May 2024

Abstract
Temporary plugging and diversion fracturing technology is an essential approach in the development of shale oil and gas. Enhancing the shear strength of temporary plugging zone is crucial for the success of this technology, which significantly depends on the geometric and mechanical characteristics of the plugging particle. Based on the rolling resistance model, this study uses Particle Flow Code (PFC) to establish a shear model for the temporary plugging zone. It explores the evolution of the strength of the plugging zone during shear failure through stress-strain curves. The research also reveals the mechanisms of strength variation from a microscopic perspective by integrating the force chain network structure. Furthermore, it quantitatively analyzes the influence of the friction coefficient, Young's modulus, and aspect ratio of the temporary plugging particles on the strength of the plugging zone. The results indicate that the strength of the temporary plugging zone is positively correlated with the strength of the force chains, but has a weaker relationship with the number of force chains. The greater the strength of the force chains, the higher the strength of the temporary plugging zone. The friction coefficient, Young's modulus, and aspect ratio of the particles are key factors affecting the strength of the force chains. As the friction coefficient, Young's modulus, and aspect ratio of the temporary plugging particles increase, the strength of the plugging zone initially increases and then stabilizes. The critical value for the friction coefficient is 1, for Young's modulus is 6.5 GPa, and for the aspect ratio is 2.7. The friction coefficient has the greatest impact on the strength of the plugging zone, followed by Young's modulus, while the aspect ratio has the least impact. This paper establishes a predictive model for the strength of the temporary plugging zone, clarifying the quantitative relationship between particle parameters and the strength of the plugging zone. It provides a basis for the optimal selection of particle materials and the development of new materials in the process of temporary plugging and diversion fracturing technology.
Unleashing the Potential of Advanced Diversion Techniques: Integrating Simulation and Real Case Study to Enhance Productivity in Limited Entry Slotted Liner Horizontal Completions within Tight Carbonate Reservoirs
Authors: Elhadidy Ahmed Ayman , Gabry Mohamed Adel , Thabet Samuel Adel 
Published: May 2024

Abstract
ARX is a common carbonate reservoir located in Egypt deserts. It is described as a Dolomite reservoir with tight formation, strong lateral continuity, and naturally fractures with low connectivity. The main challenges to maintaining economically viable well productivity are the heterogeneity and tightness.
The large interest in developing such low permeability reservoirs has been a direct result of the favorable economics achieved by the advancements in horizontal well drilling and stimulation technologies hold great promise to increase production by dramatically increasing the contact area with the producing interval, maximizing the drainage volume around a well and link those natural fractures network
Acid stimulation is a common technique used in oil and gas reservoirs to enhance the productivity of reservoirs. However, when horizontal wells completed with slotted liners are involved, unique challenges can arise. Horizontal wells have gained popularity due to their ability to access a larger reservoir area and increase production. Slotted liners, which consist of perforations along the wellbore, are commonly used in these wells to prevent sand intrusion. However, obstructions such as production logs, debris, or scale buildup can hinder the successful deployment of coiled tubing and acid stimulation tools.
This study investigates the challenges faced during acid stimulation of a horizontal well completed with a slotted liner, specifically focusing on a section where coiled tubing became stuck, spanning approximately 2000 ft horizontally. The study integrates software simulation of acid stimulation operations with actual well data and post operation production data to address the utilization of chemical diverter for delivering the acid stimulation to large areas that are inaccessible by coiled tubing due to obstructions in the horizontal section.
Facies Classification of Clastic Reservoirs Using Machine Learning Technique and their implication for New Drilling Opportunities
Authors: Moeen M. , Javed T. 
Published: May 2024

Abstract
This paper discusses successful implementation of machine learning techniques like Neural networks for prediction of reservoir facies in a highly variable clastic depositional area with limited core & log data. These predicted facies were then populated into the static model for robust field development and future well placement in Beta field of Middle Indus Basin, Pakistan.
In the study area, only 1 well outside the field had reservoir core data. This data and poro-perm facies were combined with log data to train the neural network (1D convolutional neural net). After getting an excellent match at known points, trained network was used to predict facies at Beta-1 well (exploratory well that discovered the field) utilizing the available well logs. Predicted facies were then distributed statistically using variogram (based on geological and depositional architecture of the area) and co-kriged with seismic amplitude distribution within the Beta field area.
The predicted facies were used as one of the inputs into the Reservoir Static model. Post modelling, favorable undrained area was identified in the Beta field and next development well was drilled. Well results showed that predicted facies matched with new well results by more than 70%. The results clearly demonstrate the effectiveness of machine learning techniques in predicting reservoir facies. This successful demonstration of facies prediction highlights the significance and power of implementation of machine learning methods when used with geological & geophysical data. This approach has allowed for better understanding of field dynamics, aided in better well placement, and ultimately improved production performance in the Beta field.
Leveraging Python in Decline Curve Analysis: Automation, Integration, and Advancements in Reservoir Management
Authors: Nukala S. T. , Kumar A. , Rajput S. , Lopes V. S. 
Published: May 2024

Abstract
Decline curve analysis (DCA) serves as a fundamental technique in the realm of oil and gas production, particularly for assessing the diminishing production rates of wells and projecting their future performance. This method entails fitting standard curves to historical production data, enabling the identification of trends that reflect the decline in production over time. By extrapolating these established curves, DCA facilitates the prediction of future well performance. It stands as a pivotal tool in estimating recoverable reserves, especially applicable in scenarios where the production history spans a sufficiently long duration to discern discernible decline patterns.
An integral technology employed in this process involves an automated Decline Curve Analysis (DCA) methodology, capable of autonomously executing on a machine with minimal human intervention and reduced error rates. The traditional DCA, rooted in Arp's equation, distinguishes three primary types of decline curves: exponential, hyperbolic, and harmonic.
This research endeavor encompasses the development of a Python-based framework by the authors and comparison of different methods, aimed at applying Decline Curve Analysis (DCA) methods to wells in a manner characterized by impartiality, systematic execution, and automation. Various methodologies for automating decline curve analysis were explored, and their outcomes were meticulously compared. This innovative approach stands in stark contrast to the conventional practice of manual DCA, which has historically dominated the industry. As the oil and gas sector transitions into the digital transformation era, the fusion of digital capabilities with traditional expertise in DCA becomes increasingly imperative. Embracing this synergy facilitates not only enhanced efficiency and accuracy but also fosters a deeper understanding of reservoir behavior and production dynamics.
Assessing structural connectivity and anthropogenic impacts on Ambystoma altamirani populations in Bosque de Agua, Central Mexico
Authors: Ruiz-Reyes Jessica , Heredia-Bobadilla Rosa Laura , Ávila-Akerberg Víctor , Tejocote-Perez Moises , Gómez-Ortiz Yuriana , Domínguez-Vega Hublester , Ramírez-Corona Fabiola , Alvarez-Lopeztello Jonas , Bolom-Huet Rene , Sunny Armando 
Published: May 2024

Abstract

Ambystoma altamirani is a microendemic amphibian limited to central Mexico, specifically the Bosque de Agua region in the Trans-Mexican Volcanic Belt, renowned for its endemic amphibian species. Anthropogenic activities such as land use change, water pollution, and the introduction of exotic species such as rainbow trout (Oncorhynchus mykiss) have substantially transformed its habitat, creating barriers that fragment it and impeding the mobility of the species and connectivity with other populations. This fragmentation poses challenges, including emerging diseases, inbreeding, limited gene flow, and a loss of genetic diversity, placing Ambystoma altamirani in national and international risk categories. The present study utilized the ENMeval and biomod2 models for environmental niche modeling (ENM) to assess the potential distribution of Ambystoma altamirani in the Bosque de Agua region. The key supporting variables include rivers, lakes, altitude, and a combination of Abies and Pinus forests, while the detrimental factors include urbanization and agriculture. Employing circuit theory (CT) and least-cost path (LCP) methodologies, this research explored structural connectivity, identifying core areas in the central region of Bosque de Agua. As migration distance decreases, the number of corridors facilitating population flow decreases. In the concluding phase, an analysis assessed the coincidence of state and federal Mexican Natural Protected Areas with core areas, revealing a lack of protection. The results of this study could lead to improved knowledge about Ambystoma altamirani, providing valuable tools for helping stakeholders formulate comprehensive strategies for species conservation.
Intravenous ketamine is ineffective compared to midazolam for treatment-resistant depression: a double-blind, randomized controlled study
Authors: Pattanaseri Keerati , Lortrakul Juthawadee , Jaisin Kankamol , Srifuengf Maytinee , Sa-nguanpanich Naratip , Viravan Natee , Pariwatcharakul Pornjira , Makarasara Wattanan , Ratta-apha Woraphat 
Published: May 2024

Abstract

Background: Studies have confirmed the rapid antidepressant action of ketamine in depressive episodes. Nevertheless, a standardized procedure for the delivery of ketamine infusion in individuals suffering from treatment-resistant depression, particularly in terms of infusion frequency and total dosage, remains undetermined. In addition, an efficacious ketamine regimen for persistent pain management involved a continuous 10-day infusion period with no notable adverse effects. Consequently, the primary objective of this study was to evaluate the antidepressant capacity of consecutive ketamine infusions spanning over three successive days, the duration of therapeutic response, and the overall safety profile of the treatment.
Methods: In this randomized controlled trial, participants aged 18-64 with treatment-resistant depression were randomized to receive either intravenous ketamine or midazolam (used as an active placebo) for 40 minutes daily over three consecutive days. Statistical analysis using repeated measures ANOVA was employed to assess the changes in the total score of the Montgomery–Åsberg Depression Rating Scale (MADRS) and the clinical global impression (CGI) from the initial assessment to 10 and 31 days post-infusion. Additionally, the duration of response and remission was evaluated using Kaplan–Meier survival analysis.
Results: Out of 33 randomisedparticipants, 20 underwent the treatment as planned. By day 10, the ketamine group had a mean reduction in MADRS score of 12.55 (95% CI = 6.70–18.09), whereas the midazolam group had a decrease of 17.22 (95% CI = 11.09–23.36). This pattern continued to day 31, with ketamine showing a mean score decrease of 13.73 (95% CI = 7.54–19.91) and midazolam a fall of 12.44 (95% CI = 5.61–19.28). Both treatments were well tolerated, with dissociative symptoms in the ketamine group being temporary and ceasing by the end of each infusion.
Conclusion: Intravenous ketamine given for 3 consecutive days did not show a notable antidepressant advantage when compared to the active placebo midazolam, highlighting the need for further research into effective treatments schedules for treatment-resistant depression.
Trial registration: NCT05026203, ClinicalTrials.gov, registered on 24/08/2021.