bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methods and Concepts to Economically Improve Sour Gas Processing by Reducing the Complexity of the Plant
Authors: Özcubukcu Kadir Kagan , Jelinek Wolfgang , Finke Jan , Hahn Wolfgang 
Published: November 2020

Abstract
With depletion and natural decline of the sour gas fields in Germany, many conventional gas sweetening plants have been abandoned for economic reasons. A study and a concept selection were conducted to identify technical and economical competitive methods for a pilot plant, compared to existing conventional sweetening plants.
Several technical literature sources, patents and processes licensed by third parties have been researched. 58 methods were identified for sour gas sweetening, 8 methods for sulfur recovery and 9 methods for tail gas treatment. These were quantitatively ranked in a decision matrix. Plant concepts were developed, and basis of design were created with the technology owners for the three most promising processes. CAPEX was determined with the vendors input. OPEX were estimated using the basis of design.
Sour gas sweetening via amines is a reliable and cost-effective method. The focus of this paper is therefore on sulfur recovery and tail gas treatment. The tail gas treatment can be eliminated by highly efficient production of elemental sulfur, sulfuric acid or gypsum directly from the sour gas sweetening unit. This leads to halving of CAPEX.
Production of wet sulfuric acid via contact process using an innovative reactor is favorized. This modular plant can be integrated in existing sweetening plants (brownfield) or used for new installations (greenfield). Due to the fully automated process and high availability, OPEX can be significantly reduced.
This work uses a structured method to screen the available processes and to rank them according to the given requirements. The evaluation method can be used for other boundary conditions. Production of sulfuric acid directly from the sweetening unit could increase the lifespan of sour gas wells.
How Deep Graph Analysis Based on Piping & Instrumentation Diagrams Can Boost the Oil & Gas Industry
Authors: Bergmann Martin , Hertling Frank , Marquardt Sebastian 
Published: November 2020

Abstract
Most oil and gas plant operators would like to benefit from a virtual plant model, or digital twin, which allows them to access important data quickly. In reality, however, many have to work from large numbers of legacy analogue Piping & Instrumentation diagrams (P&ID) that have amassed over many years. Digitizing these to achieve a productive digital twin using traditional, manual methods can be an excessively expensive and time-consuming task.
A digital processing tool like PIDGraph is a much faster, more efficient approach. It treats all analogue P&IDs, irrespective of origin, as flat images which it can scan using artificial intelligence and convert into XML compatible files; these can be directly processed by most CAE tools.
Crucially, a solution like this can not only understand the blocks of plant equipment, but also the relationships between them as expressed by their interconnecting pipes and wires. This allows the user to build applications on top of the graph structure. Typical use cases are Equipment Isolation for maintenance requirements, and Module Engineering for engineering applications.
As time goes by and more of a plant's P&ID information is added to the system, it can serve as a data anchor for contextualization applications. The content stored can include not only P&IDs, but also maintenance reports, material specifications, manufacturer data and many other types of documentation. Users will be able to navigate quickly through vast amounts of data to find the points that matter in any given situation. They can use this information to improve plant safety, optimize operations, and reduce costs.
Polymer Dispersed Systems for Conformance Improvement in Fractured Carbonate Reservoirs
Authors: Matveev Sergei , Gazizov Aidar , Gazizov Almaz 
Published: November 2020

Abstract
One of the most important challenges faced by the oil industry is to enhance oil recovery from existing reservoirs, carbonate reservoirs are more difficult to develop than terrigenous reservoirs because of fractures and caverns, various lithologies, geological heterogeneity and complex, polymorphous pore space structure. All these factors limit the use of EOR methods that are normally applied to terrigenous reservoirs.
The main drawback in waterflooding carbonate reservoirs is premature water encroachment in production wells because of injection water breakthrough through the most permeable and productive layers and zones, often leaving entire formations and zones unswept or almost unswept while injected water preferentially flows through already swept zones and channels.
The essence of the PDS technology consists in alternating injections of a polymer solution and a dispersed suspension that form polymer dispersed systems in the reservoir to plug swept, water-saturated layers and channels with low flow resistance and thus produce hard-to-recover oil from less permeable zones by improving the sweep efficiency.
Pilot well treatment operations using a polymer dispersed system were carried out in injection well 5 of the Zabegalovskoe field. After the first PDS treatment, the oil production rate gradually increased by 120 B/D and the water cut in the area decreased by 14%. After the second PDS treatment, the oil production rate increased by 420 B/D and the water cut decreased by 16%.
The use of the PDS technology in the area for one year and one month resulted in an incremental oil production of 71,539 bbl and reduced water production by 39,948 bbl.
Seismic Facies Classification using Generative Topographic Mapping – A Case Study from Offshore Nova Scotia
Authors: Ray Amit Kumar , Dandapani Rajeshwaran , Verma Sumit 
Published: November 2020

Summary
One of the major objectives of seismic interpretation is to effectively predict the distribution of reservoir facies away from well control. With the advent of increasing number of meaningful seismic attributes, it is time consuming and laborious to analyze them through conventional analytical methods. Machine learning techniques analyze higher dimensional data points faster and effectively. Automated seismic facies classification techniques are increasingly becoming important in identifying the potential hydrocarbon bearing zone and favorable facies. Such facies classification techniques, or, automated clustering algorithms, help arrange similar seismic traces based on the waveform shape, amplitude, phase, frequency, and other relevant seismic attributes. The main objective of automated facies classification using machine learning techniques is to perform facies classification fast and efficiently using several relevant seismic attributes for mapping the facies distribution and effective identification of the sweet spots.
The automated clustering algorithms fall into two categories – supervised and unsupervised algorithms. Unsupervised machine learning algorithms are purely data driven and help in recognizing and classifying the patterns from a dataset without any a priori information. A posteriori information such as well data, is integrated into the results for recognizing the facies classification and calibrating the interpretation. Unsupervised learning methods also help to highlight subtle stratigraphic features that might otherwise be unnoticed using conventional analytical methods.
In this study, we adopted a recent unsupervised classification technique called, generative topographic mapping (GTM). We applied this technique to a dataset from Offshore Nova Scotia, to extract the natural clusters from the seismic data for facies classification. Using the GTM technique applied to seismic data, we were able to map the distribution of different facies and potential sweet spots in the study area.
Modified Technique to Model Volatile Oil Reservoirs: Implications for Modern Software Programs
Authors: Ibrahim Mohamed , H. El-Banbi Ahmed 
Published: November 2020

Abstract
Volatile oil reservoirs are usually found in deeper geological formations. These reservoirs have become more important in recent years with advancement in drilling technology. Traditional material balance techniques used for performance prediction in black-oil reservoirs (e.g. Tarner's method described in Appendix-A) are not usually adequate to handle volatile oil reservoirs. A more appropriate technique is the one introduced by Walsh as in Appendix-B using the Modified black-oil (MBO) material balance equation. In this paper, a modification is introduced to expand Walsh technique applications. Both the traditional and the MBO prediction techniques were compared for many actual volatile oil fluid samples using compositional reservoir simulation. Comparison of the three methods revealed that the use of traditional techniques can introduce errors up to 35% when compared with results obtained from compositional reservoir simulation. The error increases with increasing volatility of the fluid and with less historical data available to perform prediction calculations. The Modified Walsh technique (presented in this paper) consistently produced results with less than 5% error when compared with compositional simulation results, however normal Walsh equation showed 10 % error. Tarner's and Modified Walsh's prediction methods produce close results for low solution gas and their results deviate significantly when volatility increases. Therefore, the Modified Walsh prediction method coupled with the generalized material balance can be used for any fluid type reservoir.
The three techniques were compared again for two actual field cases (one considered black-oil reservoir and another volatile oil reservoir). Both field cases were under depletion drive. Tarner's and Modified Walsh's prediction methods showed reasonable match with the actual performance for the black-oil reservoir, but only the Modified Walsh method could provide very good match with the actual field prediction for the volatile oil case. Using the traditional method for the volatile oil reservoir showed deviation of more than 35% in some parts of the historical data.
Flow Numerical Simulation of Tubing or Casing Leakage in Gas Well
Authors: Zhang Hong , Yuan Guangjie , Li Guotao , Li Jingcui , Wan Jifang , Fu Pan 
Published: November 2020

Abstract
Tubing or casing leakage of HTHP gas wells and underground gas storage wells affects wellbore integrity adversely. The wellbore micro-leakage detection technology can detect tiny fluid leakage in time and is of great significance to avoid malignant gas leakage accident. The theoretical basis of wellbore micro-leakage detection technology is characterizing the leakage flow field. To reveal the flow characteristics of gas leakage due to tubing and casing cracks and perforations, a CFD model of gas aperture leak has been established and flow field numerical simulation of high-speed and high-pressure gas outflow through aperture was conducted. The standard k-ɛ turbulence model was used to calculate and analyze the pressure and velocity distribution of the steady flow field. In addition, a time step was set on the steady-state model and the Scale-Adaptive Simulation (SAS) model was adopted to simulate the transient flow field with the initial conditions of the steady-state simulation results. The effects of the shape and size of the leakage hole, the pressure inside the pipe, and the medium in the outer annular space on the flow field were analyzed. The results show that obvious turbulence disturbance appears near the inlet of the leakage hole and supersonic under-expansion jet forms near the outlet of the leakage hole under the gas well working conditions, creating the expansion wave and shock wave. The flow velocity of gas leakage through the circular hole is the highest, while that of the slot hole is the lowest under the same conditions. The larger the leakage aperture is, the greater the pressure difference between inside and outside of the pipe is, and the more drastic variation of gas velocity in the leakage hole. The method and results provide theoretical guidance for the microleakage detection technology of gas well wellbore.
Inflow Control Devices ICD – A Historical Performance Analysis
Authors: Emegano Theodore Chinedu , Baloch Shahid Ali , Al. Alrefaai Mhd. Maher , Al Nuimi Saber Mubarak , Radwan El Sayeed 
Published: November 2020

Abstract
Inflow Control Devices (ICDs) and their variants autonomous inflow control devices (AICDs) have been deployed in horizontal wells in the onshore asset for more than thirteen years. The technology was adopted for their utility to manage: well inflows, sweep efficiencies, pressure drops along the well trajectory and delay fluid breakthroughs. Also, they are adapted to partially isolate fractures and or high permeability streaks which might introduce abnormal flow conditions in the production system-if unchecked. Horizontal wells were favourable target application, due to the notorious "heel-to-toe-effect" replete in horizontal wells, which ICDs are typically designed to remedy.
In the onshore asset, approximately fifty-one horizontal wells have been completed with ICDs or combination of ICDs-AICDs and some of them fully equipped for future open/close intervention capability using sliding side doors (SSDs). In this paper, a full assessment of ICDs design methodology and post installation performance over the 13-year period of ICD completions history is conducted. The performance evaluations entails ascertaining the extent to which the key design objectives are achived and overall value addition. Value based decision criteria for future ICD completion/ deployment is advocated. A proposal is submitted for further investingation into formulating universal or objective performance index (which will be independent of production data) for all well types. Such studies will include a single objective function capable of utilizing cross correlation values irrespective of well type to generate single KPI fuction.
Further recommendation (from experience) in the asset is that a do-nothing-after-completion scenario is not the best forward strategy. Greater value will be derived if ICDs completions have hindsight on ultramodern optimization post installation. Flexibility to optimize the wells in changing scenarios should be considered and built into the completion system from inception. Also the decision to adopt inflow control devices must simultaneously consider preperformance evaluation after installation. Hence data from offset wells, analougues or pre ICD performance of the study wells are input of utmost necessity for design and performance evaluation. Conclusively, a unified key performance indicator (KPI) for both ICD-completed producers and injectors is recommended for further investigation.
Performance Evaluation of Novel Perforation with Consistent Hole and Deep Penetration
Authors: Li Kai , Huang Penggang , Liu Yuan , Guo Hongzhi , Chang Cheng , Wang Bin , Li Yuanhua 
Published: November 2020

Abstract
Plug and perforation technique is the predominant method for multistage horizontal completion widely used in unconventional or tight reservoir applications. Perforation quality in such circumstances has a significant influence on completion efficiency. However, perforation performance is often described with an API RP 19B Section 1 test and not always analyzed thoroughly during the actual application. In this paper, we present several examples that qualitatively analyze perforation performance via operation data.
In the plug and perf method for multistage completions, the purpose of the perforation is to create a fluid entry point for hydraulic fracturing of each stage after the previous lateral section is isolated by plugs. In many fields, the initiation and extension of the fracture could be a critical issue and significantly slow down operations onsite. Theoretical analysis shows that perforation penetration and the effective hole number can lower the fracture pressure significantly, particularly in tectonic regions where stress anisotropy is at a high level. A novel perforation technique with consistent holes and deep penetration was tested and evaluated in several projects and it showed unique features applicable to reducing fracturing challenges. Three examples were reviewed to demonstrate that downhole perforation performance can be analyzed quantitatively through breakdown pressure comparison, pressure standard deviation analysis, and fracture extension hardness. This approach clearly showed that the novel perforation technique has advantages over traditional perforations.
Better perforations with consistent hole size and deep penetration are valuable for multistage completions in unconventional or tight reservoir applications. All the case studies in the paper show improved efficiency during multistage fracturing and completion execution. The analytical method introduced can also be easily adapted to evaluate and compare perforation quality in most multistage completion conditions.
Enhancing Reservoir Management by the Successful Drilling and Installation of a Dual Lateral Completion
Authors: Alshamsi Al Anoud , Yanez Hernandez Eglier , Zidan Maher , Al-Sereidi Amnah , Sanyal Subrata , Al-Harbi Ahmed , Mudgal Abhay , Beaman Daniel , Rondon Leonque , Butler Ben 
Published: November 2020

AbstractThe challenges of high heterogeneous multi-layer reservoirs were a driver for ADNOC to establish new well completion requirements. Based on this, the well completion strategy was revised in order to improve the completion design for a Dual Oil Producer (DOP) initially well planned without accessibility into the upper drain. The solution was successfully implemented by drilling the well having a Multilateral Dual String Level 5 Completion System to have full reservoir isolation and mechanical accessibility to TD in both drains.A major approach was implemented giving the utmost importance to all operational risks concerning drilling and completion. The design relies on the Latch Coupling (LC) pre-installed with the production casing as the foundation for the successful drilling and cementing the upper drain liner and for different completion runs. Thus, a level 5 multi-lateral completion coupled with Inflow Control Devices and Pre-perforated Liner in the upper and lower lateral respectively was successfully deployed.The main advantages of this technology compared to the initial proposal are:Brings effectively two single wells from one slot of the wellhead tower as it provides independent access & control for enhanced reservoir management (well stimulation, production logging and water shut-off). Substantial cost savings due to the utilization of one slot only. Conventional single designs need two slots to deliver equivalent completion requirements. The completion technology meets the Well Integrity Policy & Completion Guidelines stated by ADNOC to have full accessibility to all drains.This is the first Level 5 configuration installed in UAE integrated with a lower completion. The design enhances the benefits of the multilateral construction by providing full mechanical & pressure isolation at the junction throughout the life of the well. Furthermore, accessibility to both laterals from surface without the use of a re-entry deflector or any constraints was deemed to be paramount for a successful well construction.
Predictive Modelling of Drilling Fluid Rheology: Numerical, Analytical, Experimental and Statistical Studies of Marsh Funnel Flow
Authors: Ofoche Paul , Noynaert Samuel 
Published: November 2020

Abstract
This paper presents a two-parameter approach, using only density and Marsh funnel time for providing a complete rheological analysis of fluids, encompassing all six standard dial readings as established in the American Petroleum Institute (API) Recommended Practice 13D. The scope of the study includes experimental, analytical, numerical and statistical analyses of flow in the Marsh funnel. A mathematical analysis is developed based on the Marsh funnel’s geometry and a wide suite of machine learning algorithms are applied to model and predict rheological profiles across the funnel.
commercially available numerical simulation software is applied to build a model using computational fluid dynamics. Results from the numerical analysis are corroborated by analytical calculations that are then used to develop a statistical framework for predicting dial readings under various shear rates (3-600 RPM). Experimental results from more than 1500 mud tests are utilized to build ten machine learning algorithms modelling the rheological properties of the fluids. Their performances are evaluated to determine the best models based on three metrics: R-squared values, root mean square error and mean absolute error.
Predictions are performed on new mud data and comparisons are made among the ten predictive models broadly categorized into generalized regression models, decision tree-based techniques and miscellaneous approaches. The models show high predictive accuracies on new drilling fluid samples with the performances generally improving with increasing shear rates. A mathematical analysis of the geometry of the Marsh funnel has been utilized to establish a methodology to quickly and accurately perform rheological studies on fluids. Results from experimental, analytical, numerical and statistical studies all closely agree with each other.
The outcome of this study can readily be employed at the wellsite to obtain much value from the routine hourly Marsh funnel readings. This can serve as a quick substitute to infrequent conventional rheometer outputs, which are typically obtained only one to four times per day at the field. The rheological results and other derivates such as plastic viscosity (PV) and yield point (YP) are immediately produced after each Marsh funnel test. Informed decisions such as updating hydraulics modelling to improve ROP and hole cleaning can be thus be achieved. This work engages the disciplines of rheology and machine learning to produce a result that enhances the workflow during drilling operations.
Added value is derived from an already existing tool to better monitor fluid properties frequently, which is beneficial to the overall surveillance of the drilling fluid system.
Combining Augmented Intelligence and Edge Analytics for Improved Artificial Lift Systems Performance
Authors: Saghir Fahd , Gilabert Helenio , Boujonnier Matthieu , Bissuel-Beauvais Loryne , Boguslawski Bartosz 
Published: November 2020

Abstract
With the advent of IIoT enabled Edge Analytics, and its ability to run Machine Learning based inference at the extremities of a production network, it has become essential to enable Operators and Subject Matter Experts to transfer their knowledge to Edge Computing Devices.
This paper discusses the application of Edge Analytics enabled Augmented Intelligence for wells operated by Electric Submersible Pumps, where Machine Learning and Pattern Recognition Models help detect anomalous events in multivariate time-series data. These Models runs on Edge Computing Devices where identify newly discovered and well known ESP performance patterns that can be labelled by a Subject Matter Expert. Once these patterns are identified and tagged, the Models are retrained and pushed back to the Edge Computing Device, where they continue to detect and predict patterns in real-time.