bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Intelligent Intermittent Pumping Production Technology Based on Fusion of Photovoltaic Unit and Storage Battery
Authors: Zhang Xishun , Wang Cai , Sun Yizhen , Zhao Ruidong , Shi Junfeng , Yu Yanwen , Ma Gaoqiang , Li Manping , Li Shuangtao , Shen Zhenkun , Xu Jingwen 
Published: February 2024

Abstract
Intermittent pumping for low-producing wells can greatly improve system efficiency and reduce consumption. In order to further make full use of green energy and reduce carbon emission, a set of intelligent photovoltaic microgrid controller is added to the existing intelligent intermittent pumping IOT device. Moreover, an intelligent technology combining intermittent pumping and energy supply fusion of photovoltaic and storage battery driving DC motor is proposed.
The installed power of photovoltaic system and energy storage system is optimized by building a linear integral programming model of photovoltaic-energy storage-load. The optimization method can assist controller in optimizing the intermittent pumping scheme. The photovoltaic-storage intelligent microgrid controller has the function of MPPT, which can be conducted together with the frequency converter control cabinet to replace the function of photovoltaic inverter realizing the direct access of photovoltaic DC voltage to the control cabinet. The technology is based on the electric parameter data of photovoltaic, load, energy storage and other IOT data such as dynamometer card. Combining reservoir, wellbore, equipment and other data and regarding production-energy consumption-operation as the optimization objective function, a real-time optimization method based on self-learning/self-upgrading machine learning model is built. At the same time, the dynamic frequency conversion method is used to optimize the stroke automatically, realizing the adaptive control and flexible operation. The method makes full use of electricity and realizes the integrated control of photovoltaic power consumption and intelligent operation.
The method has been applied into more than 510 wells. Compared with continuous production, the average system efficiency is increased by 4.2 percentage points, the average annual electricity saving is 14.68 million kwh, the annual photovoltaic power generation is 21 million kwh, the carbon emission is reduced by 20,900 tons, the annual oil increase is more than 12,000 tons. Moreover, the manual labor is greatly reduced and the work connotation of oil workers is reshaped which improve development quality and efficiency and promote green and low-carbon development strategy.
This technology effectively solves the problems of real-time optimization of intermittent pumping, real time control, multi-energy complementary optimization forming a green low-cost intelligent intermittent pumping technology system.
The Study of Hydrogen Loss Due to Geochemical Interactions in Depleted Carbonate Hydrocarbon Reservoirs
Authors: Lino Angelo Kennedy Limaluka , Elakneswaran Yogarajah , Hiroyoshi Naoki , Abu-Al-Saud Moataz , Cha Dong Kyu , Ayirala Subhash 
Published: February 2024

Abstract
As hydrogen's role in decarbonizing energy, transportation, and heavy industry expands, it is projected that hydrogen will replace at least 3% of global fossil fuel consumption by the end of this decade. To support this growth, it’s essential to develop larger, safer, and more affordable storage facilities through underground hydrogen storage (UHS). In this study, we investigated the effects of reservoir condition and mineralogy on H2-brine-rock (HBR) system interactions necessary for quantifying hydrogen loss in depleted carbonate hydrocarbon reservoirs and predicting the UHS performance. Static batch simulations of the HBR system thermodynamics were performed in PHREEQC-MATLAB for an extensive range of pressure, temperature, brine, and mineral samples. The results show that, firstly, the influence of formation brine on hydrogen loss is minimal; secondly, temperatures and pressures exceeding 70°C and 23 MPa exhibited hydrogen stability in limestone formations; and thirdly, reservoir pressure exhibited a slightly stronger influence than temperature on hydrogen loss rates under the same mineral composition. Lastly, the result suggests that optimally a pressure of approximately 20 MPa, coupled with temperatures ranging from 90-130°C, represents an equilibrium conducive to stable hydrogen storage within depleted hydrocarbon limestone reservoirs. These findings emphasize the potential viability of UHS in such geological contexts and provide motivation and a basis for investigating the system dynamics.
Aspect-Ratio-Dependent Pore-Size Distribution from MICP Measurement
Authors: Ma Juntao , Liang Lin , AI-Hamad Mohammed Fadhel , Van Steene Marie , Ma Shouxiang Mark , Abdallah Wael 
Published: February 2024

AbstractPore size distribution (PSD) is one of the most important properties for characterizing the pore systems of porous media. Typically, a single aspect ratio (α_), defined as the ratio of the short-axis diameter over the long-axis diameter of a pore, is assumed (i.e., set to 1.0) when calculating PSD from mercury injection capillary pressure (MICP) data. This assumption implies that pores can be modeled as cylindrical tubes. In carbonate rocks, the pore network is complex and comprises multiple pore systems with varying values of α_. The objective of this study is to quantify the effect of α_ on PSD derived from MICP measurements.To achieve that objective, we initially characterize pores with different pore systems (multimodal) with different α_, which is measured from high-resolution digital images or derived from sonic measurements. The α_ distribution from digital images can be grouped into two (bimodal) or three (trimodal) pore systems, with the average α_ for each pore system being calculated. Next, we establish the relationship between capillary pressure (Pc), semi-long axis (a), and α_ for elliptical tubes. This relationship is used to transfer Pc to values of a representing different pore size. We then derive individual PSDs for each pore system by automatically selecting the best-fit combination of pore volume (PV)-based or frequency-based probability density distributions based on MICP data.We apply the proposed method to two MICP datasets, in which the corresponding α_ measurements from digital images indicate the presence of multimodal pore systems. An experiment-based analytical method and a multi-Gaussian decomposition method were executed for comparison. The results demonstrate that the proposed method provides a better fit to MICP data compared to traditional methods. This improvement arises from its consideration of α_ when converting Pc to pore size. In addition, one challenge with experiment-based analytical methods is that they are not directly based on PSD, and the fitting parameters (such as the Thomeer pore geometrical factor, G) may not be sufficient to describe the complex geometrical characteristics. On the other hand, the multi-Gaussian decomposition method assumes PV-based Gaussian distributions, overlooking frequency-based and other distribution types (e.g., uniform, triangular, beta, gamma, etc.), which the results of the proposed method have been shown to be necessary. By using the proposed method, additional pore-structure parameters, including the fractal dimension describing pore network tortuosity and volume fractions of each pore system, are also obtained during inversion. This yields detailed characterization information on the pore network. By incorporating α_ into the process of converting Pc to pore throat sizes and deriving individual PSDs for each pore system, more details of PSD are revealed, leading to improved reservoir characterization.
Development of Two Robust Data-Driven Models Using Machine Learning and Artificial Neural Network Methods to Predict Wells Fluid Rate in a Challenging Offshore Brown Field
Authors: Eldessouky M. E. , Darwish A. M. , Mohamed I. I. , Abdelhalem T. H. , Khalil A. K. 
Published: February 2024

Abstract
Two robust data driven models based on machine learning (ML) and artificial neural network (ANN) methods were introduced to overcome the shortcomings of physical and virtual well testing in Gulf of Suez offshore fields. The aim of these new models is to use the existing data and create a precise/easily accessible tool that fill the gap in well monitoring and testing system to predict wells fluid rate, improve field optimization and properly allocate oil production.
A comprehensive methodology was applied to build/verify a robust virtual model as following: 1) Analyzing General Energy Equation to select the relevant inputs, 2) Data Collection, 3) Exploratory Data Analysis (EDA), 4) Feature Engineering, 5) Machine Learning Model Selection, 6) Hyper-parameters Fine Tuning, 7) Developing Artificial Neural Network model, 8) Models Deployment.
Exploratory Data Analysis (EDA) and the General Energy Equation were used to select ten main parameters affecting the model’s accuracy. The selected features include wellhead pressure, wellhead temperature, reservoir temperature, reservoir pressure, water gravity, difference between reservoir and bubble point pressure, watercut percent, injection gas, downstream pressure, and tubing type.
Different machine learning models based on linear, support vector machine, decision trees and gradient boosting methods were programmed. The results of these models were compared based on coefficient of determination (R2 score), root mean square error (rmse), mean absolute error (mae), and mean absolute percentage error (mape). XGboost regressor was selected as the best model, then the model hyper parameters were fine-tuned using grid search method. The final model results of test dataset showed R2 score, rmse, mae and mape of 0.9674, 323, 227 and 13.1% respectively.
Furthermore, ANN was created and fine-tuned to select the model architecture. The model was evaluated using the same train and test data where the model showed comparable results to the best ML models. The results of ANN model showed R2 score, rmse, mae and mape of 0.9603, 357, 241 and 13.7%. respectively.
Reliable EACN Determination for Dead and Live Crude in Microemulsion Systems
Authors: Yoga H. F. , Gasimli N. R. , Johns R. T. 
Published: February 2024

Abstract
A successful surfactant flood maximizes oil recovery by achieving ultralow oil/water interfacial tension at the optimum salinity (S*). Optimum salinity, among other parameters, is dependent on the equivalent alkane carbon number (EACN) of the oil pseudocomponent. This paper compares common EACN determination methods used for dead crude at ambient pressure and then proposes a third more consistent and reliable method that simultaneously fits data from both methods. The first method is based on a linear plot of S* and EACN of pure alkanes, where the dead crude EACN is linearly interpolated using the measured lnS* of the crude. The second method determines the crude EACN by iteration until the measured lnS* of the dead crude and all dilution measurements become nearly linear. For live oil, the EACN is based on the common linear EACN mixing rule but corrected for pressure.
The results show that inconsistencies in estimated crude EACN using the common two methods are resolved when regression is made on all data simultaneously and when an unbiased estimate of optimum salinity is made using HLD-NAC theory, where the inverse of three-phase solubility is linear with lnS*. No nonlinear behavior is observed when fit this way and using the simple graphical approach, as has been reported in the literature using the same data. The graphical approach determines the optimal salinity based on the intersection of the linear regressions of inverse oil and water solubility with lnS*. This approach has the advantage that the optimum is unbiased, and its uncertainty is easily estimated. Using a combination of ambient and high-pressure data, we also show that the EACN of the live oil can be estimated using a methane ACN of 1.0, as it should physically be, when the effect of pressure is properly included.
First Horizontal Deployment of Remedial Conformable Sand Control Technology in Colombia - Qualification and Case Study
Authors: Stewart S. , Bermudez J. , Mazo C. , Miri R. , Salimi M. , Nouri A. 
Published: February 2024

Abstract
Remedial sand control is challenging as the solution must pass through restrictions in the upper completion then ideally conform to the inner diameter of the zone requiring sand control. This paper describes the qualification of a multi-layer, open cell matrix polymer (OCMP) solution for the first horizontal deployment in an offshore gas well.
Initial sand retention testing was conducted using a specially designed apparatus that allowed the OCMP to be evaluated at different levels of compression using formation sand suspended in water. The next set of tests were then conducted using equipment capable of replicating field gas flow rate through the optimized OCMP to evaluate sand retention, plugging and erosion. In this case, a sand pack was generated using commercially available sands and clays matched to the formation sand particle size distribution to replicate near wellbore conditions.
It was observed in the initial tests when applying 50% compression, that the OCMP was effective at retaining sand with minimal additional pressure with only 0.026lb/ft2 sand passing throughout the duration of the test. Similar results were seen in the second set of tests where there was zero sand production and no indication of plugging observed neither during the retention tests or after pressure cycling. Erosion of the outer OCMP layer was observed but was filled with sand preventing further erosion of the inner layer. Compatibility with common oilfield fluids including oil, brine, solvents, hydrochloric acid, and hydrofluoric acid was also conducted with no material degradation being experienced. It was concluded that the system was suitable for the application, and it is the intention to deploy the OCMP system on all 3 wells.
This paper introduces, for the first time, an innovative solution capable of being deployed remedially through tight tubing restrictions while providing conformant sand control in a horizontal wellbore without the need for gravel packing making the solution particularly valuable for scenarios where surface space is limited.
Static Adsorption of Novel Synthesized Zwitterionic Surfactant: A Mineralogical Study
Authors: Mohanad Fahmi , Alotaibi Mohammed , Gbadamosi Afeez , Patil Shirish , Kalam Shams , Kamal Muhammad Shahzad , Shakil Syed Muhammad 
Published: February 2024

Abstract
Surfactant flooding process is used to enhance pore scale displacement efficiency in oil reservoir. Usually, minimal retention of surfactant is coveted to achieve an efficient chemical flooding process. This adsorption behavior of a novel synthesized zwitterionic surfactant on reservoir rocks (limestone, sandstone, and dolomite) was investigated in this study. Moreover, the surfactant adsorption behavior on clay mineral was studied. The static adsorption experiment was carried out by mixing 1 g of rock sample with 15 ml of surfactant. The mixture was centrifuged and the supernatant was quantified using HPLC. The result indicates that the surfactant adsorption increases as a function of surfactant concentration. The zwitterionic surfactant displayed lower adsorption on carbonate and dolomite rock samples recording ≈ 1.068 mg/g-rock and 1.389 mg/g-rock, respectively. On the other hand, the hydroxysulfobetaine zwitterionic surfactant displayed higher adsorption on clay mineral. The mechanism of the zwitterionic surfactant adsorption is elucidated. Overall, the outcome of this study extends the frontier of knowledge on zwitterionic surfactant application for chemical enhanced oil recovery.
Accelerating Learning in the Unconventionals Through Integrated Field Experiments
Authors: Benish T. G. , Brown J. S, , Decker K. K. , Habrial J. D. , Liang Y. , Manchanda R. , Meier H. A. , Solomou A. , Srinivasan K. , Vice D. S. 
Published: February 2024

Abstract
This paper provides an overview of unconventional field experiments that ExxonMobil has conducted in recent years to measure the dimensions of fractures generated in the subsurface. These learnings are combined with production analysis to support and inform development decisions to avoid overcapitalization from suboptimal spacing, stacking, or stimulation choices.
Specific field experiments exemplify the importance of experimental design and instrumentation, as well as associated deployment challenges. Highlighted are the benefits of dedicated monitor wells equipped with fiber optics and pressure gauge arrays to interrogate the three-dimensional fracture network. While challenging to execute, this approach provides definitive measurements of the extent and variability of fracture dimensions and depleted rock volume, and requires the integration of downhole measurements, interpretation, and tool automation.
Vertical monitor wells are effective in determining the overall height of the created fractures as well as the drainage boundaries of individual benches. Slant monitor wells extend these measurements of fracture density and depletion at varying distances from a stimulated well to enable mapping of the fracture drainage network. Systematic variation of the completion design along the treatment well adjacent to a slant monitor well can be implemented to directly compare the efficacy of treatment design options in the same well.
To handle the large amounts of collected data from field experiments, automation of diagnostics workflows and integration of the data in a single tool become imperative. Pressure measurements are integrated with fiber optic measurements to provide a holistic interpretation of the extent and heterogeneity of the stimulated rock volume.
Due to their complexity and cost, instrumented slant monitor wells are rarely executed. A summary of multiple field trials are provided here where well designs, deployment, data collection, and integrated analysis were used to aid development planning and optimization.
Understanding Pore Scale Emulsification During Surfactant Injection: A Visualization of Emulsion Formation Using Microchips and Core Flooding Visualizing Cell
Authors: Alyousef M. , Alade O. S. , Al Hamad J. , Al-Abdrabalnabi R. , Al Ramadhan A. 
Published: February 2024

Abstract
Utilizing a surfactant solution to create an emulsion in a rock's pore space has been proven to enhance heavy oil production. By obstructing some of the pores in the rock, fingering is reduced, and micro-displacement efficiency is improved, ultimately increasing oil recovery. This technique is also valuable in reducing the interfacial tension between oil and water by inducing phase dispersion and altering the physical characteristics of the oil in the reservoir. While previous research has concentrated on increasing oil recovery through in-situ emulsion, there has not been much exploration into the pore-scale level of emulsion formation and its impact on recovery performance. Our study aims to explore the effectiveness of polyvinyl alcohol (PVA) surfactant as an emulsifying agent for medium to heavy crude oil, leading to the formation of water-oil emulsions. Our methodology involves injecting formation water into the microchip using a pump to achieve initial water saturation and adding oil to attain irreducible water saturation. Lastly, we will introduce the PVA surfactant to the chip and use image processing software "ImageJ" to analyze images throughout the process to gather valuable insights about its performance compared to alkaline injection. During the microfluidics experiment, it was observed that introducing PVA surfactant to the system resulted in the recovery of 27.8% of the Initial Oil in Place (IOIP). In contrast, alkaline injection yielded a lower recovery factor of 20.5%. This is attributed to the superior emulsion formation capabilities of PVA injection, leading to increased droplets, which caused blockage and prevented micro water channel formation, ultimately increasing the recovery factor. Notably, when the experiment was conducted under reservoir conditions, the recovery factor of the PVA surfactant decreased to 17.5%. However, it still demonstrated the ability to form emulsions. PVA surfactant was found to be a favorable option as it did not cause any damage or alteration to the rock sample, as confirmed by Scanning Electron Microscopy (SEM). The SEM analysis showed no change to the rock sample before and after conditioning with the surfactant for one week. Therefore, based on these findings, PVA surfactant is deemed a viable and practical option along with other surfactant types, such as Anionic surfactants, for enhanced oil recovery. The results suggest that PVA surfactant injection presents superior emulsion formation capabilities compared to alkaline injection. It is recommended that further research be conducted to explore further potential applications of PVA surfactants in EOR.
What Low Frequency Distributed Acoustic Sensing Revealed of The Hydraulic Fracturing in Tight Oil Reservoir: Ordos Case Study
Authors: Qi Yin , Zhang Tongwu , Chen Qiang , Ma Bing , Bai Jie , Ye Kai , Tang Jie 
Published: February 2024

Abstract
Real-time low-frequency distributed acoustic sensing (LF-DAS) data was acquired using a cemented, permanent fiber optic cable for the first time during hydraulic fracturing of the offset horizontal well in Ordos tight oil reservoir. Based on high-quality LF-DAS data, cross-well communication (CWC) analysis was done stage by stage while completing the treatment well using plug-and-perforating (PnP). Clear frac-hit responses were observed during each stage's treatment, and most fractures hit the offset fiber well very early, which was far beyond the operator's knowledge and triggered a rethinking of the current completion and stimulation plan. Diagnostic tools like sealed wellbore pressure monitoring (SWPM) and microseismic mapping validated the frac hit events. Reactivation responses of the fractures created in early stages were easy to identify and aid in evaluating stage isolation effectiveness. After this case, further work could be considered from qualitative results to quantitative outputs.