bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on Continuous Monitoring Technology of Fiber-Optic Production Profiling
Authors: Xu Jianguo , Yang Qinghai , Sun Wei , Duan Yongwei , Huang Hui , Liu Yazhen , Xuan Gaoliang , Xu Gege 
Published: October 2023

Abstract
At present, the distributed fiber-optic production profiling testing technology mainly adopts the permanent casing and coiled tubing well running process, which is difficult to construct and the operating cost is high, making it impossible to be applied in scale. Moreover, it can only be carried out in short-term and single test, and cannot continuously monitor the dynamic changes of oil well production for a long time.
In this paper, a technology of continuous monitoring of production profile by optical fiber is proposed. The optical cable is bundled outside the oil pipe in the production well, and is lowered below the production layer. After the normal production of the well, multiple DTS sensor logging can be carried out according to the production demand to get the contribution rate of each layer and the dynamic change of production in the whole well. This technology has the characteristics of mature well-entering method, wide range of applicable well types, low risk and cost, and capable of long-term continuous monitoring.
This technology has been successfully applied in one production well in Jilin Oilfield. The target depth range of the test well was 586.8-639m, and the cable was run down the string in just 2.5 hours. 6 hours of shut-in temperature data was taken after completion; 8.5 hours of operating well temperature data was taken after normal production. Based on the fiber-optic logging DTS data, the reservoir-wellbore coupling model was established, and the model was inverted to obtain the production profile. Under the well opening production system, the production contribution of the 586.8-588.6m, 595-603m, 608-613m, 617.2-625.6m and 632-639m segments was 6.05%, 22.18%, 24.62%, 26.74% and 20.41%, respectively. Through optical fiber logging, the contribution of small layers in this well was obtained, which provided the data basis for reservoir analysis and development strategy adjustment. Since the cable is permanent, continuous monitoring can be carried out according to the development needs to understand the dynamic changes in the production of each small layer.
The technology has been proven to be feasible in vertical wells, and further optimization and improvement can make it possible to be used to monitor the production profile of horizontal wells, which changes the situation of the lack of low-cost and effective production profile testing technology of horizontal Wells.
Pore-Network Simulations of Gas-Water Two Phases Flow in Organic-Rich and Inorganic-Rich Shale
Authors: Wang Yong , Zhou Houjie , Cai Jingshun , Zhao Yulong , Zheng Jian , Zhou Hao , Zhang Tao , Tian Hongzhao 
Published: October 2023

Abstract
Focused ion beam scanning electron microscopy (FIB-SEM) is an effective method to investigate the pore structure and gas flow in shale. Insufficient investigations have been carried out with regard to the distinctions between the inorganic-rich and organic-rich samples in the flow simulation. In this work, we selected an organic-rich sample and an inorganic-rich sample for high-resolution three-dimensional imaging, and the organic pores and inorganic pores were effectively extracted using an improved digital rock processing method. Subsequently, the pore network model (PNM) of the two samples were generated separately. Finally, the pore network simulation method was introduced to calculate the flow capacity of the two samples. Data analysis shows that the inorganic-rich sample have a higher pore radius and throat radius and a larger shape factor, with more irregular pores. While the organic-rich sample have a higher average coordination number and better connectivity. The absolute permeability of the inorganic-rich sample is larger, at 1.46 × 10−7μm2, while that of the organic-rich sample is 1.05 × 10−7μm2. The capillary pressure curve of the inorganic-rich sample is lower than that of the organic-rich sample, exhibiting a lower drainage pressure PT and a longer liquid-invasion segment. Compared to previous pore network flow simulation methods, we set a uniform gas-wet surface with an advanced angle of 100-110° for the organic-rich sample, and an advanced angle of 20-30° for the inorganic-rich sample. Forced water injection was used to simulate the water (fracturing fluid) injection process in the organic-rich sample. Due to the hydrophobicity of the pores, the gas flow capacity during water injection was quite poor, but it was improved during drainage process. In contrast, due to the hydrophilic of the inorganic pores, the inorganic-rich sample exhibited spontaneous water imbibition during the water injection process. However, the inorganic-rich sample demonstrated higher residual gas saturation during the drainage process, which indicates that fracturing fluid flowback in inorganic pores is more difficult. This work emphasizes the importance of studying the real pore structure of inorganic pores in FIB-SEM experiments, which provides fundamental insights for the description of shale gas reservoirs and the simulation of gas-water two phase flow.
Gas/Water Transient Rate Analysis and Parameters Evaluation by Integrating Pseudopressure-Based Approach with Deep-Learning Method
Authors: Wang Junlei 
Published: October 2023

Abstract
Traditional transient rate analysis (RTA) based on single-phase flow equation has been limited to two-phase gas/water flow case. The primary complication associated with the adaptation of these single-phase solutions to wells exhibiting two-phase flow is the significant difference of gas/water PVT properties and the interaction between pressure and saturation during depletion process. As a result, the material-balance time based on single-phase assumption is not practical for analyzing two-phase flow from gas wells with gas/water flow characteristics. Meanwhile, there is still a lack of an automatic interpretation model on unknown parameters through history matching with measured production data, which increases RTA application threshold in the field of multiphase production data analysis.
This work presents an integrated method of forward modeling of production performance and inverse interpretation of unknown parameters in the depletion-driven reservoirs. In the forward part, the gas/water-phase integral transformations including pseudopressure and beta factor are proposed to handle the two-phase nonlinearities in the governing flow equations of gas and water phases. The rescaled well-performance equations subject to variable operating conditions are presented through integrating the existing single-phase liquid formations with Duhamel convolution. The normalized gas/water-phase pseudopressure and material-balance pseudotime are introduced to meet the benchmark requirement of using single-phase liquid type curves. In the inverse part, an automatic interpretation model of gas/water RTA is established based on one-dimensional convolutional neural network (CNN). CNN-based proxy model is built through training large synthetic data set from forward model. Automatic inversion of the parameters is completed by minimizing the fitness function from the loss between proxy model and measured data with the help of optimization-based algorithm. The new method is validated against numerical simulation, covering a wide range of fluid properties and operation constraints.
Surfactants Structured by Nanoparticles to Stabilize CO2 Foam at High Temperature
Authors: Karadkar Prasad , Ali Shahid , Shehri Tamim , Harbi Bader , Alsakkaf Mohammed , Mansha Muhammad , Khan Safyan 
Published: October 2023

Abstract
Foamed fracturing fluids offer an attractive alternative over conventional stimulation fluids, particularly in water-sensitive formations, to shorten the flowback period and energize the created fracture geometry. The thermal stability of foam at high temperatures is one of the main challenges. The gas-liquid interface of foam tends to collapse with temperature. In this paper, CO2 foam stability is enhanced by nanoparticles structurally supporting foaming agents at high temperature.
Nanoparticles (NPs) have a tendency to stabilize foam formulations under harsh conditions of temperature and salinity. In this study, different sizes of SiO2 NPs (7 nm, 30 nm) were utilized to enhance the stability of CO2 foam. The NPs were characterized by various techniques such as XRD, TEM, DLS, and BET surface area measurements. The foaming characteristics of various formulations were analyzed by a dynamic foam analyzer (DFA-100), respectively. Rheological properties of CO2-based foams were measured by circulating flow loop foam rheometer at high temperature (250 °F) and shear rate up to 500 1/s.
CO2 foam stability is enhanced by optimizing the concentrations of CTAB surfactant and silica nanoparticles at high temperature. According to XRD findings, CS-7 and CS-30 are amorphous materials with hexagonal crystal structure. The average diameter of CS-7 and CS-30 silica NPs, as shown by FETEM images, is 12 nm and 25 nm, respectively. CS-7 has a surface area (SBET) that is 2.27 times more than CS-30 sample. CS-7 silica NPs were confirmed to have a more uniform shape, a smaller particle size, and a larger surface area based on these findings. Both CS-7 NPs and the CS-7+CTAB formulation have zeta potential values of -36.9 and 42.1 mV, which support the stability of the foamed colloidal suspension and the development of a densely packed particle arrangement at the liquid/gas interface, respectively. The foam analysis results demonstrate that adding CS-7 silica nanoparticles (0.005 weight percent) to a CO2-based formulation increases foam stability by up to 12%, demonstrating the ability of nanoparticles to stabilize foam formulations. The NPs stabilized CO2 foamed fluids’ rheological characteristics exhibited 12 cp at 100 1/s utilizing water as the external phase at 2000 pressure and 250°F.
Maintaining the stability of CO2 foam was a challenging task, especially at high temperatures. The stability of CO2 foam greatly depends upon the optimum hydrophilic-lipophilic balance (HLB) of surfactants. This was achieved by optimizing various formulations using suitable CTAB surfactant and silica NPs to overcome water drainage, CO2 gas diffusion rate, and rupturing of foam at high temperatures.
Investigating Pore Body, Pore Throat, Nano-Pore Wettability Preference in Several Unconventional Kuwaiti Carbonate Reservoirs
Authors: Al-Sayegh Saleh , Flori Ralph E. , Alajaj Hussain , Al-Bazzaz Waleed Hussien 
Published: October 2023

Abstract
This study will investigate measuring the wettability contact angles of native unconventional tight carbonate as well as other unconventional pore system reservoir samples that hosts varied pore shapes and subsequent wettability contact angle distributions in both reservoir matrix and possible natural fractures. Also, the investigation will include validation of the grain/ pore-wall wettability regions and classify the natural wettability preference available inside pores of the rock and their overall wettability performance and recovery efficiency contributions. Further investigation will include modeling pore throat contact angle wettability, and to understand their new physics that will advance reservoir characterization and oil recovery improvement.
Geomechanical Modeling and Fractures Permeability Analysis to Identify Critically Stressed Natural Fractures and the Best Well Orientation for Optimum Production
Authors: Asadi Sadegh , White Adrian 
Published: October 2023

Abstract
Natural fractures influence fluid flow into or out of formations. This may take place under in situ conditions but is more likely under stimulated conditions. How fractures behave depends on the natural fracture properties and geomechanical state of the field. If the natural fractures can retain the enhanced permeability due to shear slip brought about by injection, then the pressure-stimulated natural fractures can contribute significantly to production enhancement. To assess the impacts of natural fractures in an intended operation, it is essential to characterise the natural fractures, relate their properties with the geomechanical conditions and model their responses to changing geomechanics during fluid injection (drilling, stimulation) or production.
This study aims to characterise natural fracture permeability under in situ stress conditions to determine the best well orientation in order to intersect the greatest number of critically stressed fractures and, ultimately, optimise productivity from future wells. Analytical modelling, considered the in situ conditions, is undertaken to calculate the downhole pressure required to initiate shear slip on well-oriented fractures, make them critically stressed and hence permeable to drilling fluid. Given knowledge of the stress state, the distribution of natural fractures, and the properties of those fractures, it was possible to select the best directions to drill a well to maximise productive contact with the reservoir.
Modelling showed that the interpreted fractures would require different pressures (from 10.8 to 16.7 pounds per gallon, ppg) to become critically stressed. Critically stressed fractures strike approximately parallel to the azimuth of the maximum horizontal stress (160°N) and dip ~60°. The interpreted fractures have a wide range of dips in different wells, ranging from horizontal to vertical whilst most of them are generally steeply-dipping. Fracture trends are predominantly NW-SE except in one well where they trend NE-SW. The best well trajectory to encounter the most permeable fractures is required to be highly deviated, 60° - 85°, and parallel to the azimuth of the minimum horizontal stress (070°N). Results showed some variations from well to well, with one well appearing to be an outlier due to the different fracture population interpreted from the image data. Wellbore trajectories were optimized to take advantage of critically stressed fractures for maximum production from the fractured reservoir.
Use of Logging While Drilling Data and Machine Learning to Predict Maximum Borehole Diameter for Multistage Completion
Authors: Khan Khaqan , Tammar Murtadha J. , Alfaraj Rima , Alidi Rayan 
Published: October 2023

Abstract
Stress-induced borehole wall failure during oil and gas wells drilling can lead to over-gauged wellbore. Borehole instability leading to excessively enlarged wellbore can not only increase risk of drilling difficulties but can also cause completions integrity issues. For instance, there is a high probability of poor cementing or compromised zonal isolation across over-gauged wellbore sections in cased and cemented completions or it can result in loss of packers sealing in open hole multi-stage (MSF) completions. Both of these inadequacies of poor cementing and insufficient packers sealing can jeopardize well stimulation operations. Hence, knowing accurate wellbore shape and diameter is critical for multistage well completion requirements.
While wireline multi-arm mechanical caliper tools can be run in open hole after drilling to get direct measurement of hole size, not always such measurements are possible due to prevailing drilling difficulties. Under such circumstances, making completion decisions become even more difficult with higher risk of failure. Moreover, a solo wireline logging run to acquire caliper data requires additional cost including rig time. The objective of this paper is to predict synthetic caliper using logging while drilling (LWD) measurements (notably azimuthal density and petrophysical properties) with the help of artificial intelligence (AI) and machine learning algorithms that can be used in place of wireline caliper data thereby saving rig and logging costs and hence reducing overall field development expenditure.
This paper describes a machine learning algorithm to predict the mechanical caliper logs using LWD data. Available LWD data for different wells were used to build a robust machine learning algorithm in Python. Different logging parameters from LWD were tested to quantify their sensitivity towards the caliper data and then predict the maximum hole diameter (Cmax) for different wells. The LWD data combines different parameters that have direct effect on the caliper log with machine learning model combining them for different wells to train the model and then predict caliper log based on these parameters. The parameters used in the prediction are gamma ray, four azimuthal photoelectric factors, sonic data, porosity, formation bulk density, four azimuthal formation densities, and mineralogy. The methodology is tested for horizonal wells drilled using 5-7/8" drill-bit. The predicted caliper is compared with measured caliper data so that it satisfies completion requirements for both MSF and cased hole completions.
Unleashing the Potential of Siliciclastic Reservoirs in the Sepinggan Carbonate Sequences, A Discovery in the South Mahakam Field, Lower Kutai Basin
Authors: Wuryanto Argo , Lauwijaya Wilsen Supriady , Yoga Thomas Yunanto , Trianto Andar , Kurniawan Firman Budi , Widiartha Rizzasila , Ramdan Dadan , Hartanto Sri , Sianturi Julfree Anto Dongan , Hidayat Rahmad , Moersidin Kelik Nugroho 
Published: October 2023

Abstract
The M-1x exploration well has successfully identified substantial hydrocarbon discoveries within the Sepinggan Deltaic Sequences (SDS) and Sepinggan Carbonate Sequences (SCS). However, investigating siliciclastic reservoirs in the shallow part of the SCS in the Mahakam PSC has been hindered by challenges associated with carbonate intervals. In this study, recent seismic reprocessing data is utilized to enhance structural predictions and reservoir characterizations, providing valuable insights for future well development.
A comprehensive suite of logging acquisitions, including pressure-fluid analysis and drill stem tests (DST), was implemented to validate the properties and extent of a mixed siliciclastic-carbonate reservoir system. Although carbonate reefs and platforms dominate the interval, this study primarily focuses on the siliciclastic layers, comprising stacked sandbars occasionally interspersed with channel formations across the shelf. Utilizing recent seismic data and attributes such as variance, impedance, and spectral decomposition, an improved understanding of horizon interpretations and fault properties, encompassing their geometry, throw, and extension, was achieved. This integrated approach, combining structural understanding, sedimentological context, and seismic attribute analysis, provides a comprehensive perspective on the distribution of siliciclastic reservoirs bounded by faults and carbonate reefs.
A detailed 3D grid geological model was constructed to visualize the reservoir distribution while considering fault geometry. This model facilitates the estimation of hydrocarbon in place and enables the identification of the influence of structural components on facies patterns and reservoir distributions. Uncertainty analysis was performed on parameters including alternative horizon interpretations, facies distribution, porosity, water saturation, and fluid contacts. Over 10 wells were meticulously selected for the development plan, utilizing a combination of static geological modeling and dynamic reservoir simulation, with the primary aim of optimizing the understanding of reservoir characteristics and achieving optimal well placement.
In conclusion, this study provides a comprehensive investigation into the hydrocarbon potential of mixed siliciclastic and carbonate environments in the South Mahakam area. The enhanced understanding of structural and sedimentological interpretations of reservoir characteristics and distribution will significantly contribute to uncertainty assessment during field development and the exploration of new areas for prospects, both within and beyond the current production field.
Decoding Contaminants. A Case study to Understand Source, Origin, and Distribution of H2S and CO2 off the Coast of Sarawak, Offshore Malaysia
Authors: Masoudi Rahim , Nayak Satyabrata , Patrick Panting Alexander Tarang , A Hamid Nuril Anwar Ahba , M Diah M Amri , Samsuri Muhammad Nazam , Hoesni Jamaal 
Published: October 2023

Abstract
In the shallow offshore region off the coast of Sarawak, Malaysia, exploration, development activities, and oil and gas production have been significantly affected by the presence of high concentrations of contaminants, mainly H2S and CO2. This has led to stranded hydrocarbon discoveries in the central Luconia area. The primary aim of this research was to uncover the origins of these contaminants and predict their distribution throughout the basin. To achieve this objective, an integrated regional petroleum system modeling approach was undertaken in the study area. The focus was on identifying the sources, origins, and distribution patterns of CO2 and H2S. By employing advanced modeling techniques and incorporating isotope analysis, this study provides valuable insights into the sources and distribution patterns of the contaminants. Based on the analysis of geochemical data and petroleum system modeling, it is suggested that the CO2 in the Sarawak basin may have originated from calcareous shale (Pre-Cycle I), coaly shale (Cycle I), and a magmatic source. Meanwhile, preliminary analysis indicates that the amount of H2S encountered in the study area could have been generated from various sources and processes. Overall, this research sheds light on the complex nature of these contaminants and lays the groundwork for a more comprehensive understanding of their origins and distribution patterns in the region.