bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clustering Intermittent Pumping: A Novel Low-Cost Intelligent Producing Method for Multiple Wells Based on Edge Computing
Authors: Wang Cai , Shi Junfeng , Zhao Ruidong , Zhu Weiquan , Li Huan , Ding Kun , Zhang Xishun , Sun Yizhen , Yu Yanwen , Zhou Xiang , Liu Xiang 
Published: February 2024

Abstract
Intermittent pumping is an effective measure to reduce energy consumption and improve system efficiency for stripping wells. To date, a intelligent control cabinet for intermittent pumping usually contains one soft starting device which is used to lower the starting electric current in case of motor failure caused by frequent well restart. The cost of intelligent control cabinet is relatively high that limits the popularization of intelligent intermittent pumping.
Thus, a novel low-cost clustering intelligent intermittent pumping technology which enables multiple wells to share one Silicon Control Rectifier (SCR) soft starter and one set of intelligent terminals is proposed. A calculation method for the intermittent pumping scheme of single well was proposed based on the principle of material balance. Moreover, a reasonable clustering intermittent pumping schedule for multiple wells was optimized using particle swarm algorithm to avoid the risk of control cabinet failures caused by simultaneous startup of multiple wells. The above algorithms were embedded into the IOTs intelligent control terminal to realize real-time perception and optimization. The core circuit of the control cabinet is composed of the soft starting side branch in parallel with the main branches of all oil wells, and the control switches of all branch circuits are intelligently sensed and controlled by the edge computing terminal.
The pilot test of one cabinet controlling three intermittent pumping wells was carried out on a targeted oil production platform. Before optimization, the pump efficiency of the three wells is 28.8%, 36.2%, and 13.7%, respectively. The optimized production time of the three wells is 49 minutes, 118 minutes, and 104 minutes, respectively. The shut-in time is 311 minutes, 242 minutes, and 256 minutes, respectively. Automatic production is achieved through the clustering intelligent control cabinet. The application results show that the clustering intermittent pumping technology reduces the total cost of control devices for three wells by 68%. The electricity saving rate of the three wells is 61%, saving about 37000 yuan per year.
The novel technology of clustering intermittent pumping fills in the blank of intelligent intermittent pumping for multiple well and greatly promotes the intelligence of oilfield sucker rod pumping system.
Machine Learning-Enabled Classification System to Screen and Rank Horizontal Wells by Sidetracking Success Criteria
Authors: BuKhamseen N. Y. , Maucec M. , Aneddame A. , Mohammadi H. H. 
Published: February 2024

Abstract
Sidetracking vertical wellbores into horizontal laterals to avoid or delay water coning is a common practice in managing oil reservoirs under water flooding. Accurately predicting if the sidetrack would improve the performance of the well (i.e., reduce water production, increase oil production, or both) represents a vital information to decide whether it is optimal to sidetrack or continue with current vertical hole and withstand the increasing water cut. In this paper, we employ algorithms of predictive analytics and machine learning (ML) on a large synthetic but realistic data set of vertical bore-holes that were converted later into sidetracks in order to predict if a sidetrack would be a success. We classify the sidetracks using ratios of cumulative oil production aggregated over different periods of time of wells before and after the sidetrack. As success criteria differ depending on business objective, multiple models were built to account for the pre-set possible scenarios. The data-driven models built were based on a binary supervised classification (successful/unsuccessful) with very good accuracy, measured with Area Under the Curve (AUC) and Receiver Operating Characteristics (ROC) scores. A large number of predictors is initially used in our model, such as well location, well configuration, well completion, normalized production data, pressure data, as well as assorted petro-physical attributes, such as reservoir quality and average saturation indices. Through an exercise of recursive feature elimination, only parameters that contribute to improve the quality of prediction are retained. Results of several classification algorithms such as decision trees and support vector machines are being studied and compared. Several developed models with cross-validation are introduced to reduce bias and variance and to render better prediction results. Applying the model on a set of test simulation data, ML model predictions of success and failure cases conform with simulated data with high level of accuracy. Additionally, predictive models were found useful in identifying parameters that highly correlate with the success or failure of sidetracks. Final results showed an accuracy as high as 80% and an AUC of the ROC curve of 0.79.
Hydrocarbon Saturation Evaluation Behind Gravel Packing and Complex Completion Through Advanced Pulsed Neutron Logging
Authors: How L. H. , Cavalleri C. , Yusuf N. , Tolioe W. A. , Daud S. H. , Johare D. , Hendrawati M. S. 
Published: February 2024

Abstract
Gravel packing in the annulus between the screen and casing ensures the production of reservoir fluids without sand production. However, the effectiveness for controlling sand production and the permeability of the pack decreases over the years. It is important to quantify the gravel packing together with formation fluids saturation evaluation for production enhancement opportunities. From pulsed neutron logging (PNL), analysis of the expanded set of elements and minerals at high accuracy allows the quantification of gravel packing and reservoir fluid saturation simultaneously.
Between two PNL runs, the background gamma ray (GR) count is subtracted from the activated GR count. The gravel pack log is made from linear response between the good gravel section and the top of gravel or major void. Besides, from inelastic-capture measurements in gravel packs, the normalization of near detector inelastic silicon yield to the sum of silicon and iron yields is another effective gravel pack quality indicator. Later in the processing path for formation evaluation, different environmental corrections and elemental offsets are determined to remove the contribution of gravel pack, different borehole fluid, and casing and cement composition. Ultimately, the integrated interpretation of carbon-oxygen (C/O), Total Organic Carbon dry weight fraction (TOC), neutron porosity (TPHI) and fast neutron cross section (FNXS) enable accurate determination of formation gas, oil, water saturation condition behind gravel pack and casing.
In three examples presented in this paper, the gravel pack (GP) quality has been addressed and analyzed based on two different methods: the traditional GR counts difference between activated and not log, and the direct estimate of gravel presence and percentage from raw elemental concentrations being measured by the advanced PNL simultaneously to the other pulsed neutron and carbon/oxygen measurements. Understanding the gravel packing and the contribution from borehole conditions will help to reduce the uncertainties of log response and to compute reliable rock petrophysical properties and fluids saturation in the formation.
The prompt evaluation of these gravel pack logs can provide a more accurate understanding of borehole effects on the petrophysical answer. The information can also directly be used to determine the void in gravel pack completions. Further plan for void repair can reduce the formation damage resulting from fluid loss in the formation.
Innovative Application of Solid Degradable Particles Mitigates Plug Failure and Efficiently Enhances Acid Fracturing Plug and Perf Operation
Authors: Albuainain Faisal , Almulhim Abdulrahman , Farias Stefano , Anwer Ibrahim 
Published: February 2024

Abstract
This methodology presents an efficient implementation of solid degradable particles to address zone isolation failures in plug and perforation (Plug and Perf) acid fracturing operations, thereby facilitating proper zone stimulation without the need for subsequent well interventions using coiled tubing or wireline.
The novel approach centers on the utilization of multi-modal, self-assembling, and self-degradable solid particles to temporarily seal the void space created by an unset ball in a mechanical plug situated between two fracturing stages. The methodology encompasses techniques for identifying isolation failures from various perspectives and outlines the necessary adjustments to transition from conventional solid degradable particle usage to align with this new approach. Additionally, a comprehensive method is presented for readers to replicate this solution in similar scenarios.
Effective stimulation of tight gas carbonate formations, particularly in high-temperature, high-stress, sour environments with reservoir heterogeneity, poses significant challenges. In addition to meticulously studying reservoir properties to select the appropriate acid blend and diverters for stimulation treatment, the completion strategy plays a pivotal role in augmenting stimulated reservoir volume.
While Plug and Perf operations have proven to be an effective solution for zone isolation, they entail additional time and costs when interventions are needed, such as addressing an unset ball within the plug.
This study focused on a horizontal well with two acid fracturing treatments, considering similar formation properties, perforation strategies and treatment fluid volumes. Based on these comparable parameters, a series of analysis were conducted to validate communication between stages through the mechanical plug. Subsequently, the methodology involved the design and efficient pumping of an appropriate solid degradable pill to isolate the path to the previously stimulated zone. Several indicators of its effectiveness were observed, including a significant pressure increase once particles began bridging and sealing off the path within the plug, an overall higher-pressure response between stages, and a substantial difference in instantaneous shut-in pressure (ISIP). These observations corroborated the effectiveness of stage isolation achieved using self-degradable solid particles, ultimately resulting in the treatment of the new non-stimulated zone.
The innovative application of solid degradable particles presented herein represents a forward-thinking solution that enhances the efficiency of Plug and Perf operations. It obviates the need for additional wireline interventions to set new plugs and contributes to improved reservoir stimulation coverage—a critical factor for the commercial recovery of hydrocarbons in carbonate tight gas reservoirs.
Characterizing Unconventional Hydrocarbon Resources Through Geochemical Analysis
Authors: Alghamdi Abdulaziz , Hassan Amjed , Mahmoud Mohamed , El-Husseiny Ammar , Abu-Mahfouz Israa S. 
Published: February 2024

Abstract
This study presents the use of geochemical analysis in order to improve the evaluation of unconventional recourses. Several parameters were studied including total organic carbon (TOC), free hydrocarbon amount (S1), potential hydrocarbon (S2), hydrogen index (HI), oxygen index (OI), pyrolyzed carbon (PC), and total sulfur content (Total S). The main objective is to understand the relationship between all these parameters and to examine the impact of thermal maturation on the geochemical variables. Organic-rich shale samples were collected and used in this work. The shale samples were maturated at different temperatures and for various durations. The Rock-Eval analysis was carried out before and after each thermal treatment in order to capture the changes in the geochemical properties.
The obtained results showed that thermal maturation can significantly change the geochemical properties, reducing the total organic carbon, increasing the S1, and reducing the HI. A reduction in the total organic carbon was observed, the TOC was reduced from around 20 to 15 and 12 wt.% after maturating the shale samples at 250 for one and two days, respectively. While the S1 was increased by three times on average due to the maturation processes. The HI was reduced from around 800 to less than 350 due to the maturation revealing that the kerogen was converted into vaporized hydrocarbon which leaves the shale and leads to the HI reduction. The vaporization of organic matter led to an increase in the rock porosity by around 4 to 8 p.u. Overall, this study confirms the importance of integrating different geochemical properties in order to improve the evaluation of unconventional resources.
Super-Virtual Interferometry for Noises Elimination in Microseismic Datasets
Authors: Zhou Yicheng , Hanafy Sherif 
Published: February 2024

Summary
In microseismic study, traces with low signal-to-noise ratio (SNR) are considered an intractable issue, especially in surface monitoring arrays. To alleviate this problem, we propose to use the supervirtual interferometry (SVI) approach to enhance the SNR of the recorded traces. The key idea is to generate diffraction gathers by convolving different traces, then calculate the common negative-positive pair gathers by correlation and convolution, and finally stack similar traces to obtain supervirtual traces with higher SNR. We tested the proposed method on 2D acoustic single-source and multiple-source cases.
PTA Modelling Approach to Accurately Assess Formation Damage Associated to Wells Completed with Inflow Control Devices
Authors: Guerrero R. J. Phillips , Akresh S. A. Bin , Alodah M. D. 
Published: February 2024

Abstract
Inflow control devices (ICDs) help enforce uniform flow profiles, in horizontal wells drilled across reservoir sections with variable permeability distributions. ICD completions are installed along the dedicated horizontal sections, inducing an additional completion related skin into the total skin factor due to the pressure drop across these tools. A numerical modelling approach in this paper will quantify the ICD related skin factor to confirm the existence of any formation damage for remedial actions if necessary.
Recent software technologies have overcome this hurdle of determining each component of the apparent damage skin (the formation damage skin and the completion skin related to ICDs) by incorporating key design parameters (i.e., ICD strength or nozzle size) of these devices into the numerical modelling. This paper will present examples where a numerical approach has been implemented to estimate the formation damage skin factor from pressure build-up tests conducted in wells equipped with ICDs. In addition, the new numerical ICD modelling approach has enabled the determination of the contributing ICD completion compartments or targeted sections, which results in accurate effective well length assessment.
This paper will show examples of modelling build up test data with conventional analytical solutions, in which well test analysts can only obtain the apparent damage skin, and therefore will not be able to de-couple each skin component (the true formation damage skin and the completion skin related to ICDs), compared to the advantages of a higher resolution numerical modeling approach which captures the complex well geometries incorporating the ICD design parameters (i.e., ICD strength or nozzle size) to quantify the true formation damage beyond these tools. This numerical modelling approach will ultimately lead to an accurate estimation of the formation damage skin factor beyond these completions and will also enable the estimation of the contributing ICD completion compartment or targeted section along the horizontal wellbore.
With the ICD numerical modeling capability in complex well geometries allowing the assessment of the true formation damage, well testing analysts will confidently take reliable actions regarding remedial stimulation jobs by knowing the magnitude of the formation damage skin and will also be able to assess the contributing ICD completion compartments or targeted segments along the drilled wellbore for a higher resolution of the effective well length estimation from the pressure transient analysis perspective.
Integrated Advanced Technologies for Heavy Oil Identification Application in Saudi Arabia
Authors: Alghareeb Abdulaziz Ahmad , Al-Sultan Athbi , Al-Dhafeeri Sultan , Santoso Gagok , Alghamdi Sarah 
Published: February 2024

Abstract
The recent horizontal well was drilled with expectations to have some residual heavy oil separated within fault block. It required precise information for both fault and structural prediction, enhanced well placement, and completion optimization. Considering the well challenge and objective, formation evaluation was highlighted as critical where the complex pore structure will play a big role in fluid mobility, viscosity, saturation, presence of tar, permeability, irreducible water saturation, and rock quality. This paper presents integrated advanced LWD technologies that help with heavy oil identification in horizontal wells.
Ultra-high-definition resistivity imaging was used to study azimuthal formation porosity distribution in order to quantify the different porosity portions (Primary / Secondary). Following that, facies determination was obtained based on porosity spectrum, amount of secondary porosity combined with relevant logging results using neural network technique. This is significant to optimize well placement in the best reservoir rock types. Other than that, the use of LWD NMR helps to determine rock typing and formation permeability profile. This qualitative interpretation is supported by advanced mud logging services and THCnorm ratio to assist interpretation of the hydrocarbon zone.
Real-time support was done to execute the well as per the objective. The well was drilled through the A and B reservoirs and confirmed the penetration of several faults and fractures. The usage of the high-resolution resistivity images confirmed the development of secondary porosity 20% higher than matric porosity. NMR provided unique fluid typing information and quantified the heavy oil viscosity variations, which could not be quantified from density/neutron or resistivity measurements. Heavy oil with a viscosity of up to 30 cP was found in the middle zone of the A Reservoir. Oil viscosity was observed to change laterally, as it varied each time the same layer was crossed. NMR also confirmed no significant presence of heavy oil in B-Reservoir. The interpretation of Advanced Mud logging confirmed hydrocarbon bearing reservoir, that has very good agreement from LWD interpretation. Effective use of the latest technologies allows for studying and improving the current formation evaluation in carbonate reservoirs.
Low Resistivity Low Contrast Saturation Evaluation Applying Anisotropic Rock Physics Model to Sonic Logs
Authors: Zharnikov T. , Vorobiev S. , Ayadiuno C. , Vorobyev V. , Akinyose O. , Ashfaq M. 
Published: February 2024

AbstractLow resistivity low contrast (LRLC) pays can contain significant additional reserves for the producing wells in decline. The most common tools for the LRLC formations analysis are triaxial resistivity and Micro-Imaging logs. However, such logs may not be available, in particular in the legacy wells. The paper describes a new method to analyze laminated reservoirs and to estimate saturation using Gamma Ray, Neutron, Density and Sonic logging suite.The method utilizes anisotropic rock physics model to analyze sand-clay lamination. The anisotropic rock physics model allows to subdivide total clay volume estimated from Gamma Ray and Neutron-Density into the laminated and the dispersed clay fractions using shear modulus. The dispersed clay behavior is described using Reuss, Upper and Lower Hashin-Shtrikman bounds. The laminated clay is accounted for through Backus averaging. When the model is calibrated, the fluid bulk modulus is extracted, and the saturation evaluation is done using Brie equation. The Brie exponent calibration method utilizing fluid bulk modulus versus total clay volume plot has been developed.The method has been tested on a number of wells including cases, where laminated reservoir presence was confirmed by alternative methods, for example by Image logs. It allows to evaluate saturation and to identify pay zones in majority of the test cases. The method limitations are heavy hydrocarbons presence, when oil bulk modulus is close to that of formation water, or the cases of heavy mud invasion on depth greater than one wavelength. The reason for the latter limitation is that the sonic logs’ depth of investigation is close to one wavelength. Thus, if invasion depth exceeds that, a sonic tool measures only residual hydrocarbons presence. With these two notorious exceptions, the method produces excellent results. The comparison of the dispersed and laminated clay volumes estimated by different methods allows to calibrate total clay content in the cases when X-ray diffraction (XRD) data is not available.The paper presents novel method for the saturation analysis in LRLC reservoirs, where just limited logging suite is available. The method utilizes anisotropic rock physics model and requires Gamma Ray, Neutron, Density, Compressional and Shear sonic logging suite.