bluuebunny/crossref_metadata_2025 huggingface dataset:
The Existence of Antipersonnel Land Mines in Aceh And Impact for Indonesia
Authors: Daudy Muhammad Heikal , Adwani  , Muazzin  , Darmawan
Published: February 2024

Purpose: This study aims to revitalize the memory of many parties regarding the existence of anti-personnel landmines in Aceh which still leaves homework to be completed even though peace is already 19 years old. These deadly objects are still found and threaten people's lives to this day. Indonesia has ratified the 1997 International Antipersonnel Landmine Convention through Law Number 20 of 2006. In fact, Indonesia is bound to implement all the provisions of the convention.
 
Theoretical framework: This study combines a number of general legal principles in international humanitarian law, with reference to the 1997 International Anti-personnel Landmine Convention.
 
Methods: The study method is adopted by combining normative and empirical legal studies, where data collection is carried out in literature and the field, with emphasis on the application of norms in conventions and their implementation in the field as far as can be observed.
 
Results and Conclusions: The results of the study show that the Government of the Republic of Indonesia does not appear to be doing its best to resolve the problems caused by the presence of anti-personnel landmines in Aceh.
Research implications: This research is urgently needed as an alternative pattern for resolving the antipersonnel land mine problem that Aceh is experiencing as part of the Republic of Indonesia.
 
Originality/value: The hope is that through this research, the experiences of a number of ASEAN countries will become best practices for the national antipersonnel landmine clearance campaign in Indonesia. ASEAN's involvement is intended to help sustain peace in Aceh in accordance with the Helsinki Memorandum of Understanding on August 15 2005 and Law of the Republic of Indonesia Number 11 of 2006 concerning the Government of Aceh.
Islamophobia and Communism: Perpetual Prejudice in Contemporary Indonesia
Authors: Waston  , Wiranto Erham Budi , Ali Mudzakir , Achmad Noor , Ramdhani Deddy , Muthoifin  , AN Andri Nirwana
Published: February 2024

Purpose: This study aims to explain the relationship between Islamophobia and the issue of Communism in Indonesia today.
 
Methods: This research is a type of Data collecting was carried out on the mass media and social media and a literature review to discover this; then, the analysis was carried out using a philosophical approach.
 
Results and Conclusion: This study found that the government policies that were seen opposing Islamism aspirations were considered a form of Islamophobia. The tendency of Islamophobia is resulted from the government and the winning party's closeness to China, especially the Chinese Communist Party, which results in the chaos of the law and efforts to reduce the ideology of the Pancasila (Five Principles). This condition presents a classic contestation between Islamism and Communism in the socio-political realm of contemporary Indonesia. In the contestation, Islamophobia continued in the form of negative imagery of Islam, Arabic, and Islamic politics. The response of Islamic groups to this condition is the strengthening of Islamism under the pretext of defending the state ideology.
 
Research implications: The Development of Islamophobia: This research can provide insight into how Islamophobia develops and is maintained in the Indonesian context, which can provide a better understanding of its root causes and potential consequences in society.
 
Impact on Interreligious and Interthought Relations: The implications of this research may go beyond political issues and touch aspects of interreligious and interthought relations in Indonesia. This can strengthen or weaken social relations between different groups.
 
Public Policy: This study can provide a basis for the development of better public policy in addressing issues related to Islamophobia and society's understanding of communism. Policies created based on this research can be aimed at promoting tolerance and social justice.
 
Further Research: This research may spark interest in further research on the same or related topics. Follow-up studies could dig deeper into the specific aspects revealed in this research or broaden the scope to understand a broader phenomenon.
 
Global Influence: The implications of this research are not only limited to Indonesia, but can also provide valuable insight into how the phenomenon of Islamophobia and the stigma against communism is developing at the global level. This can help in understanding the impact of globalization and interconnectivity in spreading ideologies and perceptions.
 
Originality/value: Insights into Political Dynamics: Through its examination of the perpetuation of prejudice, the research offers valuable insights into the political dynamics of contemporary Indonesia. By uncovering how certain narratives and ideologies are utilized and perpetuated for political purposes, the study provides a critical perspective on power dynamics and manipulation within the Indonesian contex
Effects of Farmyard Manure and Biochar Treatments on the Development and Water Use of Lettuce Under the Deficit Irrigation Regime
Authors: Erguler Dilruba , Okyay Fatma , Senol Omer , Yerli Caner
Published: February 2024

In this study, the effects of different organic matter additives [soil (control), 20 ton ha-1 farmyard manure, 20 ton ha-1 biochar, and 10 ton ha-1 farmyard manure+10 ton ha-1 biochar] to the soil of lettuce grown with different irrigation water levels [100% (full irrigation), 75% (25% deficit irrigation), 50% (50% deficit irrigation), and 25% (75% deficit irrigation)] on water and irrigation water productivity efficiencies and plant characteristics were investigated. Among the organic matter additives, the biochar reduced the amount of irrigation water and actual evapotranspiration of lettuce and increased its marketable yield, thus the highest water and irrigation water productivity efficiencies were obtained from biochar treatment. Despite the decreasing marketable yield in the 50% irrigation treatment, the proportionally decreasing amount of irrigation water and actual evapotranspiration caused the highest water and irrigation water productivity efficiencies to occur in the 50% irrigation treatment. While the root diameter, root fresh and dry weights, stem diameter and length, head fresh and dry weights, marketable leaf number and yield, chlorophyll, and leaf relative water content of lettuce decreased with decreasing irrigation water levels, root length and membrane damage increased. The effects of organic matter additives on all of these physical-physiological properties, except root diameter and membrane damage, were found to be significant, and the biochar provided the most effective development of these parameters under the deficit irrigation regime. Considering that the yield and yield characteristics in 75% irrigation treatment do not decrease at a very significant level compared to full irrigation (100%) and that these decreases can be compensated by biochar and that the farmyard manure+biochar as alternative treatment is also effective in improving the decrease in yield parameters, treatment of 10 ton ha-1 farmyard manure+10 ton ha-1 to the soil at 75% irrigation water level was found to be recommended in lettuce cultivation.
Burguesía petrolera y redistribuciones estatales: el caso de Argentina durante el gobierno de Macri (2015-2019)
Authors: Gómez Lende Sebastián
Published: February 2024

La relación entre hidrocarburos y acumulación por desposesión es muy antigua en Argentina y siempre se ha desarrollado en un marco signado por redistribuciones estatales. Este artículo describe y analiza las políticas ejecutadas por el gobierno de M. Macri (2015-2019) para apuntalar y reforzar la rentabilidad de la burguesía petrolera, utilizando para ello bibliografía académica, estadísticas oficiales e informes de organizaciones ambientalistas. El estudio se basa en cuatro categorías de análisis: colonización de organismos reguladores estatales; privilegios comerciales, fiscales y monetarios; concesión y extranjerización de áreas hidrocarburíferas; y socialización del riesgo empresario. Se concluye que la política hidrocarburífera de Macri fue un híbrido entre neoliberalismo y (neo)desarrollismo signado por conflictos de intereses entre Estado y capital, la imposición de la disciplina de mercado a los consumidores y la producción política de rentabilidad para petroleras locales y extranjeras, generando pobres resultados en materia de autoabastecimiento y soberanía energética.
The insignia of ecclesiastical authority as a subject of the arts and social sciences
Authors: Bogacka Katarzyna
Published: February 2024

Insygnia władzy kościelnej stanowią kategorię przedmiotów wyróżniających się pod wieloma względami spośród innych obiektów sztuki. Oddziaływanie na odbiorcę jest (przynajmniej potencjalnie) wielowarstwowe, a pełnione przez poszczególne insygnia funkcje społeczne, jak wykazały wcześniejsze badania, mogą się znacznie różnić. Artykuł stanowi próbę odpowiedzi na pytanie o celowość odwołania się w badaniach nad insygniami do metodologii nauk społecznych, nie tylko zaś humanistycznych i liturgiki. Postawiona została teza, że przedmioty te w ostatnich dwóch stuleciach ulegają przemianom formalnym i znaczeniowym, eksponującym ich społeczne funkcjonowanie, co ujawnić mogą badania uwzględniające problemy z zakresu nauk o komunikowaniu, psychologii i socjologii sztuki.
53. Międzynarodowy Kongres Eucharystyczny Quito 2024
Authors: Dziuba Andrzej
Published: February 2024

W ramach przygotowań do 53. Międzynarodowego Kongresu Eucharystycznego Quito 2024 odbyło się w stolicy Ekwadoru posiedzenie Papieskiego Komitetu Międzynarodowych Kongresów Eucharystycznych. Niniejsze sprawozdanie ukazuje przygotowania i zaangażowanie wokół teologii, duchowości i pobożności eucharystycznej.
Improved Reservoir Rock Porosity Prediction from Advanced Mud Gas Data
Authors: Anifowose F. , Badawood S.
Published: February 2024

In our continued effort to extend the utility of advanced mud gas (AMG) data from the traditional fluid typing to reservoir rock properties prediction, this study investigates the feasibility of predicting the full porosity log for the hydrocarbon-bearing zones of wells ahead of wireline logging and core analysis processes. Our previous incremental results have confirmed the successful prediction of missing porosity logs in an interval within the borehole and in a section of a field.

We established the linear correlation between porosity and Total Gas (TG) to confirm the hypothesis. Leveraging the capability of machine learning (ML) algorithms to recognize hidden patterns in data, we developed artificial neural network (ANN), decision trees (DT), and random forest (RF) models. We collected over 20,000 data points from representative wells in the study area, used 90% for training and optimizing the models, 10% for testing, and five wells for blind validation. A cut-off of 500 ppm was applied on the total gas to remove background gas effects and focus on the hydrocarbon-bearing zones.

Using statistical model performance evaluation metrics comprising correlation coefficient (R2) and mean squared error (MSE), we compared the results of the ANN, DT, and RF models. The RF model consistently outperformed the others based on the training, testing, and validation metrics. Using the original AMG data, the least-performing RF model gave an R2 value of 0.78 for training, 0.76 for validation, and MSE of 0.014 for full-well blind testing. After applying the cut-off, the performance of all the models improved significantly, while the RF model maintained its best performance. With this improvement, the least-performing RF model gave an R2 value of 0.98 for training, 0.89 for validation, and MSE of 0.003 for full-well blind testing. Considering the outcome of our previous studies, these results have further confirmed the robustness of nonlinear solutions based on the ML methodology. It can be concluded that the ML approach for predicting reservoir rock porosity from AMG data acquired in real time is feasible, though with room for improvement. This study also confirms the benefit of focusing on the productive zone by applying a cut-off on the TG.

This study will contribute to the objectives of digital transformation in the petroleum exploration industry by (1) expanding the utility of existing data without extra cost, (2) utilizing real-time data such as the AMG to predict rock properties in real time for better decision, (3) providing more information to optimize reservoir contact while drilling, and (4) providing information to determine reservoir quality at the early stage of well development.
Utilizing Advanced Mud Gas Data to Predict Oil Volume Fraction Using Machine Learning Algorithms
Authors: Anifowose F. , Mezghani M. , Torlov V.
Published: February 2024

Digital transformation is unleashing unprecedented potentials to maximize subsurface data utilization. Advanced mud gas data have been extensively used for reservoir fluid typing. Oil volume fraction (OVF) is traditionally obtained from core analysis and typically computed from wireline logs. Extensive core analysis is expensive and time-consuming. The underlying assumptions of the equations to compute OVF from wireline logs introduce uncertainties. This study proposes a machine learning (ML) approach to predict OVF based on advanced mud gas data to reduce uncertainties and increase accuracy.

There is currently no established empirical correlation between advanced mud gas components and OVF, which creates the opportunity to apply ML algorithms. We applied two models comprising decision tree (DT) and random forest (RF). A multivariate linear regression (MLR) model was implemented as a benchmark. Advanced mud gas data and their corresponding OVF values from 10 wells were used. The gas data comprising 16 light and heavy components are the input features. All the wells were combined to build the dataset used to train the models, leaving one out at each run for blind validation. Out of the results obtained, we present two representative ones in this paper.

We used correlation coefficient (R2) and mean squared error (MSE) as basic metrics to assess the performance of the models. The comparative analysis of the models’ performances showed that the RF model has the highest accuracy for both validation wells to predict OVF using advanced mud gas data. For well A, the RF model has a training R2 value of 0.98 and 0.79 for validation. For well B, the training and validation R2 values for the RF model are 1.0 and 0.84, respectively. The least performing model is the MLR, giving training and validation R2 values of 0.95 and 0.66 for well A and 0.95 and 0.67 for well B, respectively. This indicates that the challenge of predicting OVF using advanced mud gas data is more of nonlinear relationship that is better handled by a ML method rather than a linear model such as the MLR. The MSE for all the models are generally very low. The results also showed that the total normalized hydrocarbon is the most significant feature.

The outcome of this study shows that predicting OVF from mud gas data is feasible using the ML methodology. ML methods are capable of handling the nonlinearity of the data even when the linear correlation is weak. There is also ample room for improving the accuracy of the models by adding more real time data. This study has showed the potential to predict OVF while drilling, ahead of core analysis and wireline data interpretation.
Experimental Study on Plugging Behavior of Temporary Plugging Particles During Dynamic Increase of Fracture Width
Authors: Guo Jianchun , Zhao Feng , Ren Jichuan
Published: February 2024

Temporary Plugging fracturing technology is an effective method to increase fracture complexity in shale oil and gas development. During the temporary plugging process, the gradual increment of net pressure within the fracture leads to a progressive increase of the fracture width, ultimately rendering the temporary plugging zone ineffectual. Therefore, it is crucial to understand the plugging behavior of the temporary plugging zone as the fracture width increases. In this paper, we establish a novel plugging evaluation device capable of dynamically altering the fracture width in real time, while monitoring the plugging pressure within the fracture. The pressure response characteristics of temporary plugging zones with different particle diameters in the process of dynamic fracture width increase were understood. Finally, the influence of injection rate and viscosity on re-plugging of temporary plugging zone is studied. The findings indicate that when the fracture width reaches the critical fracture width, a distinct dominant channel forms between the temporary plugging zone and the fracture wall, causing a significant drop in plugging pressure. The critical fracture width is determined as one-third of the particle diameter, and smaller particle sizes correspond to smaller critical fracture widths. When the fracture width is below the critical fracture width, effective particle rearrangement can be achieved by increasing the injection rate and viscosity to prevent the formation of dominant channels. However, when the fracture width exceeds the critical fracture width, re-plugging the temporary plugging zone through increased injection rate or viscosity is not feasible. In such cases, the dominant channels can only be filled by pumping additional particles. This paper provides the study on the plugging characteristics of the temporary plugging zone under dynamic changes in fracture width for the first time. It proposes the critical fracture width conditions for re-plugging, which serve as a basis for selecting particle size, optimizing injection rate, and viscosity in temporary plugging and diverting fracturing.
Single Phase Retarded Acid System: Innovative Solution for Sustaining Well Productivity
Authors: Sahu Qasim. A. , Kalgonkar Rajendra. A. , Ali Eyad. A. , Alzaid Mustafa. R.
Published: February 2024

Single phase retarded acid systems have been developed as an innovative approach to enhance well productivity. This acid system is designed to maximize contact with the formation by gradually releasing acid over time, which improves well stimulation, flowback initiation, and gas production. The technology involves using minimizing the free water to retard the reaction rate of the acid, which helps to distribute it homogeneously and deeper in the formation. In addition, this acid system can be combined with hydraulic fracturing to further improve production. The use of this innovative solution has shown to be effective in sustaining well productivity and could be a promising alternative to traditional acid systems such as emulsified acid.

The development of the new acid system involves blending a mineral acid with a suitable organic acid, while minimizing the presence of free water in the formulation. This approach helps to control the dissociation of the acid and achieve the desired retardation properties. The single-phase acid system, characterized by its low viscosity, has proven to be highly effective in acid fracturing applications. To assess its potential, the technology was implemented in high temperature and high-pressure conditions, specifically targeting the fracturing of conventional gas wells completed with a plug and perf completion consisting of six stages. The driving force behind field testing was the aim to significantly enhance the fracture half-length compared to the existing standard emulsified acid system. Achieving this objective involved careful control of engineering parameters during the treatment process, as well as optimizing the acid's retardation properties. A comprehensive post-treatment analysis was conducted to evaluate the performance of this acid system, comparing it to previously tested systems. This analysis included pressure transient analysis, post-frac flowback assessments, and friction pressure calculations. Downhole gauges were installed in order to obtain accurate pressure measurements for friction calculations and Pressure Build-up (PBU) analysis. We have recently shared significant progress in the development and implementation of an innovative engineered hybrid acid system, which effectively addresses the limitations associated with the use of emulsified acids. Implementing the new acid system in acid fracturing treatment, we have achieved remarkable success, as indicated by the sustained gas production rate. The treatment outcomes have resulted in a substantial enhancement of the well’ productivity index.

This paper presents a study showcasing the successful utilization of a newly developed retarded acid system for acid fracturing applications in multistage completions. It emphasizes the key design parameters unique to this system and outlines its advantages and limitations compared to traditional retarded acid system.
Optimized Pressure Transient Acquisitions Improve Development Planning of Tight Rich Gas Fields in Sultanate of Oman
Authors: Hegazy A. M.
Published: February 2024

The main goal of this study is to evaluate the effectiveness of Pressure Transient Analysis (PTA) in tight condensate-rich gas fields in Sultanate of Oman. Initially, PTA was used to define the dynamic permeability, total skin factors, and assess impairment due to condensate banking around wellbores. However, after long periods of production, new objectives arose, including assessing impairment due to poor clean-up of fractures in depleted layers. The overall objective is to address PTA different signatures and complications and to use results to improve well and reservoir modeling for better field development planning and the hydrocarbon maturation process.

To achieve the study's objectives, about 35 PTA acquisitions were conducted in four mature clastic gas fields in Oman, which include over 250 fractured wells and have been producing gas and condensate for more than 30 years. The study involved an extensive revision of PTA results to address the main issues of these fields. The researcher estimated most of the actual fracture dynamic parameters and compared them with the corresponding designed parameters. Also, PTA results have been utilized to fine-tune dynamic permeability models, improving the reservoir pressure history matching to give more reliable forecast and development plans.

The study's results showed that proposed individual layer permeability models (controlled by PTA results) were much more reasonable, improving dynamic modeling significantly. Delayed hook-up of fractured wells led to poor fractures clean-out in pressure depleted layers, resulting in weak fracture performance. The actual fracture parameters were much lower than expected before implementation, especially for pressure depleted reservoirs. By controlling the dynamic permeability model of each layer, using PTA results, condensate banking phenomenon has been simulated clearly, considering its negative effect on wells and field production performance. The researcher matched and proved the observed PTA results and prevailing responses (fracturing, condensate-banking) using sophisticated single and Box numerical simulation models. These models were incorporated into full field simulation models, leading to significant improvements in field production forecasts and field development planning.
Consolidation of Carbonate-Based Formation Rocks by Dissolution-Precipitation of Ground Calcium Carbonate
Authors: Alarawi Abeer , AlTammar Murtadha J. , Alrubeh Jasim A.
Published: February 2024

Generating hydraulic fractures with good conductivity is essential for well productivity in unconventional formations. However, hydraulic fractures gradually lose conductivity with hydrocarbon production as fracture surfaces creep closer due to proppant embedment or failure of fracture asperities under increasing effective in-situ stresses and high temperatures. This work proposes adding a widely available, natural-based ground calcium carbonate (GCC) to fracturing treatments in carbonate formations to make fractures mechanically harder and enhance long-term well productivity. The GCC-based solutions with several particle sizes (PS of 5-30 µm) were prepared at 77-300 °F and tested on homogenous carbonate core samples. Several solutions (different PS) were formulated by mixing 20 gm of GCC powder in 100 ml of organic solvent. The core samples were immersed in different solutions for seven days at either 77 or 300 °F, and the samples were thoroughly characterized before and after exposure to the solutions. Rebound hammer tests were also conducted to show the effect of the solutions on the samples’ mechanical properties, such as Young's modulus and compressive strength. The test results show that the physical properties, such as the dry weight of all core samples, increased noticeably after treatment, reflecting the success of the precipitation reaction and the penetration of used GCC into the bulk of the rock samples. Rock treatment with several (PS of 5-30 µm) powder solutions led to a significant enhancement of the samples’ mechanical properties, where Young's modulus (E) and Unconfined Compressive Strength (UCS) were observed to increase by up to 10-25 % compared to untreated rock samples. Rock hardening in fracturing applications is a relatively new concept. Compared to the consolidation additives in the literature, the proposed GCC formula is ubiquitous, widely available, and inexpensive. Lastly, the GCC formula is a by-product of a few oilfield operations, making it a sustainable solution to industrial waste in the oil industry.
Assessing the Heavy Oil Waterflood Efficiency through Integrated Crosswell Testing and Advanced Production Analysis
Authors: Al Harty N. , Rassuli E. , Al Lawati H. , Aslanyan A. , Gulyaev D. N. , Nikonorova A. N.
Published: February 2024

The paper presents a study of a heavy oil mature field in Oman with aggressive water cut growth and slightly exceeding the ultimate recovery as per the initial Master Development Plan expectations. The reserves have been naturally depleted for more than a decade before trying out the waterflood a few years back. The first results of the waterflood were not consistent due to high cross-well interference from one side and possible compartmentalization from another.

The key objective of the current study was to assess the on-going waterflood efficiency, cross-well interference, possible production complications and assess possibility of improving further recovery. The key instrument of the cross-well interference analysis was based on multiwell deconvolution of the permanent downhole pressure gauges in response to the historical flow rate variations in offset wells. The water cut diagnostics was based on the large number of well-by-well metrics including recovery micro-modelling baselines, multiphase IPR analysis and multiphase productivity analysis. The mobile reserves’ potential was assessed through material balance, fractional flow analysis and decline curve analysis. Both watercut diagnostics and reserves evaluation have been facilitated by a digital assistant with a fully automated generator of numerous diagnostic metrics which otherwise would take an unrealistically long time to perform such a study.

The study has come to the conclusion that all wells are fairly connected but confirmed the deterioration of connectivity between a few wells. The water injectors have confirmed a fair connectivity with all surrounding producers while the aquifer was found to be much weaker than the effect from water injection in these wells. The study suggests that this field still contains commercial volumes of hydrocarbon reserves which can be economically recovered, preferably via horizontal side-tracks from existing wells. It has been recommended to repressurize two main reservoir units independently. The study has spotted a few suspects of thief water production and recommended reservoir-orientated production logging to locate the water source, which was most probably occurring behind the casing. These wells have been recommended as primary candidates for side-tracking.

The current study was extensively using a combination of bottomhole pressure deconvolution and advanced watercut diagnostics for heavy oil production to provide a holistic analysis of the remaining reserves. The study also provides the comparison of the results of pressure forecast between multiwell deconvolution technique (MDCV), artificial neural network (ANN) and capacitance-resistivity model (CRM).
CO2 as a Service (CO2aaS) Advisory and Optimization Contractual Models for Critical Production Assets
Authors: Porciani Daniele , Parrella Ilaria , Lauriola Michele
Published: February 2024

Based on the existing knowledge and capabilities of rotating equipment and critical energy systems, industry players are developing and implementing solutions for Emissions Monitoring and Optimization("EM&O") solutions, aiming advanced monitoring and advisory as well as emissions reduction targets within their Environmental, Social and Governance ("ESG") policies (e.g. Oil & Gas Methane Partnership2.0 – "OGMP 2.0" or the United States Environmental Protection Agency GreenHouse Gas Reporting Program – "GHGRP").
New Dimension to Field Wide Cement Evaluation Based on AI & ML for Pro-Active Well Integrity Management in Matured Oil and Gas Fields
Authors: Reddicharla Nagaraju , Vanam Prabhaker Reddy , Voleti Deepak Kumar , Ali Mayada Ali Sultan , Shkeili Ali Abdulla Al
Published: February 2024

Cement evaluation can be performed when well integrity log measurements are combined with the mud and cementing data. However, a truly comprehensive cement evaluation can only be performed when well integrity log measurements are combined with all available well data, including cementing, mud, drilling, geological, and petrophysical data. However, well logging results are complex and can be ambiguous, and decisions associated with significant risks may be taken based on their interpretation based on physics applied in the logging tools. This paper describes a successful application of artificial intelligence and machine learning for cement evaluation which is independent of various logging providers and reservoir conditions.

This in-house solution uses cement bond logs along with other data sets like cement quality parameters, mud parameters, drilling parameters, geological/formation markets information and well type as an input. Historical cement bond log was selection was based on leak off tests. Machine Learning Model was trained separately for each vendor such as Schlumberger, Halliburton, Baker tools with more than 30km of interpreted dataset with high confidence respectively. The ensembled Random Forest and convolution neural network models have been built and analyzed. Cement data quality process has been automated before it is used in model.

Based on predictions, well cement ranking and well integrity recommendations were designed respectively for light weight and heavy weight casing designs based on lift type. All workflows’ steps have been automated to aid process standardization across company. The cement evaluation information is integrated GIS maps for finding aerial and reservoir cross section uncertainties.

The system has resulted a good database for cement evaluation and well integrity that helped to identify potential integrity issues like possible cross flow, communication between reservoir zones with acquirers, possible fluid communication to surface

This approach has replaced manual methods and achieved 95%-time efficiency in decision making cycle. The well retirement process has been improved based on accurate results from this system. This system has helped to challenge the conventional process and been evaluated for ranking the candidates for corrosion monitoring and possible challenges related to well integrity. Workovers have been planned to carry out cement repair jobs in one of matured field for the wells with the age of more than 10 years.

This AI based tool is very cost effective, with minimum human bias, improves consistency and allows proactive well integrity management. This tool can be used to any wells/fields irrespective of their geological setting and geographic locations.
A New Method for the Reuse of Water in the Oilfield
Authors: Choudhary S. , Malekahmadi F. , Moringo N. , sie V. , Liu S. , Li Y. , Price B. , Muhamed M. , Emmanuel I.
Published: February 2024

Increasing environmental, social, and governance values and metrics in the oil and gas industry have resulted in using produced water instead of freshwater for hydraulic fracturing. Produced water has increased total dissolved solids and increased concentrations of multivalent cations compared to freshwater. The altered chemical composition of produced water leads to flocculation and decreased performance of products, specifically emulsion polymer friction reducers traditionally used in freshwater. Flocculation leads to poor regained conductivity, formation damage, and less oil production. Operators may use a higher dosage of emulsion polymer to combat the change in composition, leading to concern over cost, treatment efficacy, and environmental, social, and governance regulations. The use of produced water for hydraulic fracturing necessitates the advancement and development of products.

The compatibility of water and emulsion polymer is necessary to minimize cost and increase treatment efficacy for hydraulic fracturing. Our newly developed emulsion polymer favorably interacts with multivalent cations, resulting in excellent friction reduction in produced waters. In addition, this emulsion polymer avoids flocculation in mid and high TDS brines containing large iron concentrations. This newly developed anionic emulsion polymer is an iron tolerant friction reducer that addresses the growing challenges in utilizing produced water for hydraulic fracturing and fills the gap in the current market.
A Comparative Study on Fluid Composition Determination from Near Infrared Spectra Using Deep Convolutional Neural Networks and Partial Least Squares Regression
Authors: Weinzierl W. , Cartellieri A. , Schapotschnikow P.
Published: February 2024

The conventional approach to fluid characterization using partial least squares (PLS) is considered a benchmark in chemometric fluid analysis. Complementary, convolutional neural networks (CNN) have been shown to provide comparable discrimination capabilities. In a comparative study, the performance for quantitative characterization of downhole fluids using near-infrared (NIR) spectra has been evaluated. Both methods are used to predict the fluid composition in fractions of water, gas, oil, and mud. PLS is a statistical technique designed to model the relationship between two sets of variables, in this case between the spectrum and the composition. It relies on the representation of the variables in a multidimensional latent space. Usually, the inference consists of three steps. First, the input (spectrum) is linearly projected into the latent space. Second, the output is calculated in the latent space. Finally, the composition is computed as a linear transformation of the latent output. Instead of using PLS for end-to-end inference, only its first step has been used for feature extraction. By using the first latent dimension for each component, features were obtained that can be conveniently associated with water, gas and oil respectively. These features are then used together with the constant baseline in a multinomial logistic regression to obtain fractional components of the present fluid types in the NIR spectra. The baseline is primarily needed for mud detection. In parallel, several CNN models were trained for fluid characterization based on NIR spectra on processed and raw data. Hyper-parameter optimization of the CNN's is performed using a tree structured Parzen estimator to obtain a best trial configuration. Scheduling of the optimization loop yielded improved inference results. Quantitative comparison of the PLS and CNN models was performed using a k-fold approach. This allows for a direct comparison of the methods performance given as input spectra of pure and mixed fluids. Both methods show high accuracy when predicting pure components. The root mean square error (RMSE) is consistently larger for PLS. The CNN models generally show larger variance in the prediction for mud, with minor fractions of water, gas and oil being inferred. A quantitative comparison of two methods in chemometric fluid analysis shows an overall improvement of predictive power for a set of deep CNN in respect to the PLS approach. Improved inference is achieved using raw NIR spectral data. This is particularly interesting as no further pre-processing of the spectra is required, thereby minimizing porting efforts in the development of embedded applications.
Maximizing Value From D Field Via Safeguarding Hub Reserves and Resources For Sustainable Supply and CCS Development To Peninsular Malaysia Ecosystem
Authors: Faiz M Faridyl , Rong Tee Zhao , Samsudin Yuzairy B , Ramli Zuhairi
Published: February 2024

D Hub is one of the key offshore gas hubs currently receiving gas from several producing fields for onward supply to domestic Peninsular Malaysia customers via an existing onshore gas terminal and pipeline network. Due to production decline as well as techno-commercial challenges of future field tie-ins, D Hub was expected to reach its Minimum Compressor Limit (MCL) of 70 MMscf/d by end of 2022 below which the hub is no longer operable.

Recognizing the impending cessation of D Hub and storage availability in the range of 1.2 – 1.7 Bscf at its depleted anchor field, Carbon Capture and Storage (CCS) has been identified as a promising option to repurpose the gas hub into a CCS hub. Moreover, interests in low carbon industry are accelerating in Malaysia, with CCS as one of the key enablers to meet Net Zero Carbon Emission (NZCE) commitments.

The technical team has also identified seven (7) solutions ranging from short-, mid- and long-term to further sustain D Hub existing operations either by lowering down its turndown limit and/or maturing new gas supply developments. The success of either of these initiatives however will further push the timing of the CCS hub conversion.

The paper is split into three (3) parts: -

In the first part, the solutions identified to extend D hub as gas hub will be described in detail. Short term solutions to ensure D Hub can continue operation includes the commissioning of Module Recycle Valve (MRV), lowering down D Hub plant pressure and production enhancement for the existing producing fields. Mid-term approaches consist of maturing projects with higher technical certainties and restaging the compressor to a lower turndown limit while waiting for a major Gas Cap Blow Down (GCBD) project to achieve higher project maturation (long term solution).

The second part will discuss the CCS Hub key challenges and considerations, mainly revolving around CO2 injection timing at D Hub.

Then finally the last part of this paper will outline the conundrum faced in choosing whether to further extend the gas hub at the expense of CCS deferment or an earlier CCS but at the risk of future gas developments being stranded.
New Generation Fracturing Fluid with Superior Proppant Transport and Oil Displacement Functionalities
Authors: Lin Genyao , Huang Jiangshui , Richardi Bryant , Yu Stephanie , Li Jianshen , Liu Fuchen , Lin Lijun
Published: February 2024

Multifunctional fracturing fluid is desirable in the oil and gas industry as it can simplify hydraulic fracturing operations and reduce environmental impact. Traditional high-viscosity fluids, like borate crosslinked fluid, can effectively transport proppant to keep fractures open but can constrain fracture length and damage the proppant pack. Conversely, low-viscosity options like linear gels, can extend fracture length and facilitate secondary fractures, but have limited proppant carrying capabilities. Recent efforts have attempted to combine fracturing fluid with surfactants to achieve both hydraulic fracturing and improved oil recovery. However, these efforts require multiple additives and still lack sufficient proppant transportation. This study introduces a new generation fracturing fluid combining superior proppant transport and oil displacement functionalities, formulated with a unique polymer containing chemically bonded oil displacement surfactant.

The new fracturing fluid was evaluated using a range of tests, including static proppant suspension test, rheology test, coreflood, regained conductivity and oil displacement tests. The static proppant suspension test compared the new fracturing fluid with a linear gel. The fluid's rheological properties were measured using an advanced rheometer. The spontaneous imbibition Amott test was conducted to appraise the fluid's oil displacement properties. The coreflood and regained conductivity studies were conducted at 160°F to evaluate the fluid's formation and proppant pack damage.

The new generation fracturing fluid excelled in all tests studied. In the static proppant suspension test, it suspended the 20-40 mesh ceramic proppant much longer than the traditional guar-based fluid. The rheology test revealed that the 0.3wt% fluid's storage modulus G’ is higher than the loss modulus G" across the whole spectrum of frequency tested, signifying high elasticity of the fluid. The spontaneous imbibition test demonstrated the new fluid increased the relative oil recovery rate by 12.1% compared to the control polymer. The coreflood results showed an 85.7% regained permeability for the 0.4wt% new fluid. The conductivity study showed a 94.7% regained conductivity. These results demonstrate that the next generation fracturing fluid can not only offer superior proppant transport capability but also it can be easily broken down by traditional breaker and then release the oil displacement surfactant to achieve oil displacement functionality. These features make the new fracturing fluid an excellent choice for hydraulic fracturing applications with less freshwater usage and reduced environmental impact.
Application of a New Imaging Technique in Thin Beds Analysis / Sand Counting of Clastic Reservoirs in Oil Base Mud Environment
Authors: Ighodalo Endurance , Idris Umar , Hassan El-Saied , Al Mubarak Mustafa Ahmad
Published: February 2024

The identification and quantification of thin bedded net reservoirs is very challenging. Accurate pay thickness requires the integration of high-resolution data. This paper presents an accurate pay estimation method in wells drilled with Oil Base Mud (OBM) across clastic reservoirs where high-resolution image and true formation resistivity logs were utilized to perform advance thin bed analysis.

OBM image technology provides photorealistic borehole image, electrical conductivity, and dielectric permittivity. Gauss-Newton algorithm is applied to generate button standoff, formation resistivity and dielectric permittivity images. Also, the new Hayman factor image analysis associates colour spectrum to the various rock and fluid types in the formation. This was used in estimating the reservoir heterogeneity, including open or closed fractures and more importantly the thin beds sand counting. The true formation resistivity was utilized to optimize the saturation / pay across these thin beds. These static measurements are integrated with dynamic results from the formation testing.

Quantitative analysis of Advanced OBM Image data across thinly bedded clastic reservoirs has been conducted. Lamination analysis of the high-resolution image data was performed to understand the lamination density and thickness. The inverted resistivity image was applied to differentiate the good quality sand from degraded facies. Both analysis results were integrated with the true formation resistivity to evaluate accurate net pay in thinly bedded sands and subsequently confirmed by hydrocarbon samples.

The technique presented in this paper reveals new and accurate method to evaluate and estimate the amount of reservoir heterogeneity. These will help in a more precise estimation of net sand / pay count in thinly bedded sands.
An Integrated Engineering Approach Aiding the Delivery of the Challenging Build-up and Lateral Sections in an Exploration Field
Authors: Baghdadi Ahmed , Sen Souvik , Chakrabarti Prajit , Vossen Johannes , Malik Kashif , Salmin Ivan , Bashir Munir , Bakr Ahmed
Published: February 2024

This study presents a case of successful delivery of a challenging build-up and lateral section through heterogenous lithologies from an exploration field in the Middle East using an integrated multidisciplinary approach of optimization, planning and execution. Based on the offset well drilling experiences, poor ROP, mechanical instability, and differential sticking against some of the highly porous and permeable carbonate reservoirs were identified as the main drilling challenges impacting delivery for the 8-1/2" and 6-1/8" sections parallel to the regional minimum horizontal stress azimuth. Comprehensive geomechanical modeling and wellbore stability analyses were carried out to recommend a safe mud weight window to tackle mechanical instabilities. Utilizing an optimum drill bit design ensured improved durability, trajectory control, a higher rate of penetration and resulted in a 33 % performance improvement on the field average. Drilling fluid chemistry was optimized with required bridging concentrations based on particle size distribution assessment. The 7" liner shoe placement and drilling practices were optimized based on the offset well events and subsurface characteristics to ensure successful execution of the landing section. Real-time monitoring of the LWD data (includes density imaging), aided by right-time geomechanical advisory support ensured successful well delivery without any significant drilling challenges. As a result of the implementation of this systematic and integrated multidisciplinary approach, both sections achieved geological objectives with zero NPT. The well was delivered 8.6 days ahead of the plan, and 14 days ahead of the best similar well.