bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quasi-urbanizacja obszarów wiejskich (na przykładzie Dolnego Śląska)
Authors: Becla Agnieszka , Czaja Stanisław 
Published: March 2021

Artykuł przedstawia proces quasi-urbanizacji na obszarach wiejskich. Autorzy zidentyfikowali formy przebiegu tego procesu. Są to:

– zmiana struktury sektorowej lokalnej gospodarki, – zmiana form aktywności zawodowej ludności, – zmiana źródeł dochodów ludności, – tworzenie quasi-miejskiej infrastruktury,
– zanik produkcji rolniczej, – rozwój aktywności pozagospodarczej.
Autorzy rozpoznali również główne przyczyny tego procesu. Badania objęły Dolny Śląsk. Autorzy określili główne rodzaje osad na terenach wiejskich: 1) letniska i wczasowiska, 2) wsie-sypialnie, 3) wsie usługowo- -rolnicze, 4) wsie usługowo-przemysłowe, 5) wsie usługowo-przemysłowo-rolnicze oraz 6) wsie wyludnione.
A Robust Artificial Intelligence Method for Predicting Performance of Offshore Oilfield in High Water Cut Period Based on Big Data
Authors: Ma Kuiqian , Chen Cunliang , Zhang Wei , Liu Bin , Han Xiaodong 
Published: March 2021

Abstract
Performance prediction is one of the important contents of oilfield development. It is also an important content affecting investment decision-making, especially for offshore oilfields with large investment. At present, most oilfields in China have entered high water cut stage or even extra high water cut stage, which requires higher prediction accuracy. Water drive curve is an important method for predicting performance. Traditional methods are based on exponential formulas, but these methods have poor adaptability in high water cut period. Because traditional methods deviate from straight line in high water cut period.
In this paper, a robust method for predicting performance of offshore oilfield in high water cut period based on big data and artificial intelligence is proposed. Firstly, the reasons for the "upward warping" phenomenon of traditional methods deviating from the straight line are analyzed. It is found that the main reason for the deviation is that the relationship between the relative permeability ratio of oil to water and the water saturation curve no longer conforms to the exponential relationship. So a new percolation characteristic characterization equation with stronger adaptability is proposed, which focuses on the limit of high water flooding development. On this basis, the equation of the new water drive characteristic curve is deduced theoretically, and the dynamic prediction method is established. What's more, the solution of the method is based on large data and AI algorithm.
This method has been applied to many high water flooding phase permeability curves, and the coincidence rate is more than 95.6%. The new water drive characteristic curve can better reflect the percolation characteristics of high water cut reservoirs. At the same time, the performance of adjustment wells and measures on the curve of development dynamic image is analyzed. Curve warping indicates that adjustment wells or measures are effective. Field application shows that the prediction error of the new method is less than 6%, which is more in line with the needs of oilfield development. Because of the application of artificial intelligence algorithm, the application is more convenient and saves a lot of time and money. This is a process of self-learning and self-improvement. As the oil field continues over time, each actual data will be recalculated into the database. Then the fitting and correction are carried out, and then the solution is learned again.
This method has been applied to several oil fields in Bohai. And the effect is remarkable, which provides a good reference for the development of other oil fields.
The Role of Fossil Fuels in a Hydrogen Economy
Authors: Lau Hon Chung 
Published: March 2021

Abstract
The world of energy is transitioning from one based on fossil-fuels to one based on renewable energies and hydrogen as an energy carrier. At present, only 11% of the world's final energy consumption and less than 1% of industrial hydrogen come from renewable energies. Our analysis shows that this energy transition will take several decades because of two factors. First, renewable energies give more CO2 savings in replacing fossil fuels in the power sector than producing hydrogen for heat generation in the industry sector. Therefore, significant quantities of green hydrogen will not be available until renewable energies have replaced fossil fuels in power generation. This will take at least two decades for advanced economies and twice as long for developing economies. Second, even if blue hydrogen produced by fossil fuels with carbon capture and storage (CCS) is available in large quantities, it is still more expensive than blue fossil fuels which is also decarbonized by CCS. Consequently, fossil fuels and CCS will continue to play a key role in this energy transition. To accelerate this energy transition, governments should introduce a significant carbon tax or carbon credit to incentivize companies to implement large-scale CCS projects. Nations whose governments adopt such policies will go through this energy transition faster and benefit from the associated job creation and economic opportunities.
Salt Drilling: The State of the Art
Authors: Campbell Scott , Bueno Ricardo , Eren Sinasi , Abdullah Malik Faisal 
Published: March 2021

Abstract
Drilling though salt is not a new challenge in the petroleum industry, with successful exploration and appraisal wells in salt environments paving the way for complex field developments. A detailed summary of how these advancements have subsequently evolved into the technology and methods being used today is presented.
The numerous challenges, and the resulting solutions, of drilling in salt environments are well documented; a comprehensive review of the relevant published industry literature has been conducted. Additionally, workshops with several major service vendors have been held to ascertain the current status of research and new product development. These two areas form the foundation of this work and have been weaved together and presented to establish what is the state of the art in salt drilling.
Since the first salt wells were drilled, the drilling industry has changed considerably. Significant advancements in salt drilling technologies and methods have been made in areas such as: best drilling practices, salt formation geomechanics, salt formation geochemistry, drilling fluids, well cementing, directional drilling, drill string and drill bit design. These advancements have all been clearly delineated in a chronology of continuous improvement, compounded by the considerable weight of industry experience and lessons learned which has in turn led to optimisation, and increased efficiency, of salt drilling operations. Today, salt drilling is prevalent in areas such as the Gulf of Mexico, deep-water offshore Brazil, and deep-water West Africa, where the boundaries are continually pushed due to the perseverance of both petroleum operating companies and service vendors.
The existing body of literature on salt wells is large and covers many disciplines of the upstream business, from wildcat exploration through to production. However, this focus is solely on drilling, combining and summarising many years’ worth of experience, learning, research, and development, to present what is the state of the art in salt drilling.
Successful Polymer Treatment of Offshore Oil Well Suffering from Sand Production Problems
Authors: Zaitoun Alain , Templier Arnaud , Bouillot Jerome , Salehi Nazanin , Wijaya Budi Rivai , Wijaya Agung Arief , Witjaksono Arief , Kurniadi Wery 
Published: March 2021

Abstract
Many fields in South East Asia are suffering from sand production problems due to sensitive sandstone formation. Sand production increases with time and increasing water production. The production of sand induces loss of production, due to sand accumulation in the wellbore, and heavy operational costs such as frequent sand cleaning jobs, pump replacements, replacement of surface and downhole equipment, etc. An original sand control technology consisting of polymers injection and already deployed in gas wells, has been successfully tested in an offshore oil well.
The technology utilizes polymers having a natural tendency to coat the surface of the pores by a thin gel-like film of around 1 µm. Contrary to the use of resins which aim at creating a solid around the wellbore, the polymer system maintains the center of the pores fully open for fluid flow, thus preserving oil or gas permeability while often reducing water permeability (a property known as RPM for Relative Permeability Modification). The advantage of such system is that the product can be injected in the bullhead mode and often, a reduction of water production is observed along the drop in sand production. In gas wells, the treatment lasts around 4 years and can be renewed periodically.
A lab work was undertaken to screen out a polymer product well suited to actual reservoir conditions. We conducted bulk tests to evaluate product interaction on reservoir sand samples, and corefloods to evaluate in-situ performances. Treatment volume and concentration were determined after lab test.
One of "Oil Well" candidate is located in Arjuna Field, offshore Indonesia. Downhole conditions are: Temperature = 178°F, salinity = 18000 ppmTDS, permeability = 140-300mD, two perforated intervals with total thickness of 67ft (ft-MD) with 38 ft Average Netpay Thickness, production rate = 800 bfpd. The well is under gas lift and needed to be cleaned out every 3 months because of sand accumulation.
Polymer treatment was performed in two stages (bottom, then upper interval). A total volume of 150 m3 of polymer solution was pumped. Immediately after treatment, sand cut dropped from 1% to almost 0%. This enabled increasing the drawdown from 32/64’’ choke to 40/64’’, keeping the production sand free and sustained with time.
This field test confirms the feasibility of the original sand control polymer technology both in gas wells and in oil wells, which opens high possibilities in the future.
Closed-Loop Data Analytics for Wells Construction Management in Real Time Centre
Authors: Rosli Azlesham , Mak Whye Jin , Richard Bobbywadi , Meor Hashim Meor M , Arriffin M Faris , Mohamad Azlan 
Published: March 2021

Abstract
The execution phase of the wells technical assurance process is a critical procedure where the drilling operation commences and the well planning program is implemented. During drilling operations, the real-time drilling data are streamed to a real-time centre where it is constantly monitored by a dedicated team of monitoring specialists. If any potential issues or possible opportunities arise, the team will communicate with the operation team on rig for an intervention. This workflow is further enhanced by digital initiatives via big data analytics implementation in PETRONAS. The Digital Standing Instruction to Driller (Digital SID) is a drilling operational procedures documentation tool meant to improve the current process by digitalizing information exchange between office and rig site. Boasting multi-operation usage, it is made fit to context and despite its automated generation, this tool allows flexibility for the operation team to customize the content and more importantly, monitor the execution in real-time. Another tool used in the real-time monitoring platform is the dynamic monitoring drilling system where it allows real-time drilling data to be more intuitive and gives the benefit of foresight. The dynamic nature of the system means that it will update existing roadmaps with extensive real-time data as they come in, hence improving its accuracy as we drill further. Furthermore, an automated drilling key performance indicator (KPI) and performance benchmarking system measures drilling performance to uncover areas of improvement. This will serve as the benchmark for further optimization. On top of that, an artificial intelligence (AI) driven Wells Augmented Stuck Pipe Indicator (WASP) is deployed in the real-time monitoring platform to improve the capability of monitoring specialists to identify stuck pipe symptoms way earlier before the occurrence of the incident. This proactive approach is an improvement to the current process workflow which is less timely and possibly missing the intervention opportunity. These four tools are integrated seamlessly with the real-time monitoring platform hence improving the project management efficiency during the execution phase. The tools are envisioned to offer an agile and efficient process workflow by integrating and tapering down multiple applications in different environments into a single web-based platform which enables better collaboration and faster decision making.
Determination the Levels of Thief Zones Based on Machine Learning
Authors: Lu Chunhua , Jiang Hanqiao , You Chengcheng , Wang Fulong , Xu Fei , Li Junjian 
Published: March 2021

Abstract
The technique of interwell tracer testing is considered as one of the most effective method to identify the thief zone (TZ) in reservoirs. However, in heavy oil reservoirs, tracer breakthrough curves are mostly parabolic and unimodal, thus resulting in slight differences between curves. It is inefficient and inaccurate to identify different types of curves with traditional methods applied to characterize the levels of TZs. In this paper, convolutional neural network (CNN) is applied to construct a classification model for the automatic identification of the levers of TZs. According to the TZs criteria specified on the field, the analytical tracer transport model was applied to generate 3000 curves as the sample, which can meet the requirements of model training accuracy. In the meantime, One-hot encoding, Xavier initialization, Adam optimizer, and mini-batch normalization were used to construct the model, and the key parameters are optimized to improve the performance of the model. The results show that the appropriate activation function is ReLU and the optimal dropout rate is 0.5. Moreover, the construction of CNN with discrete data points (DDP-CNN) as input contributed to a further improvement of classification accuracy of tracer curves. The accuracy of DDP-CNN in training set is 0.96, which is 14% and 23% higher than random forest (RF) and k-means, respectively. In practical applications, DDP-CNN proves capable to correctly classify 88 of the 100 curves.
Real-Time Down-Hole Monitoring of Gas Injection Profile Using Fibre-Optic Distribute Temperature and Acoustic Sensing in Tarim
Authors: Chen Defei , Huang Kun , Meng Xiangjuan , Liu Ju , Zhang Bao , Sun Tao , Shen Jianxin , Wei Junhui , Wu Hongjun , Teng Qi 
Published: March 2021

Abstract
Gas injection has become an important means of enhancing oil recovery (EOR) in clastic reservoirs, the Donghe Oilfield, Tarim, has been undergoing gas injection to enhanced oil recovery. During the gas injection, dynamic justification of gas injection was the most severe challenges, which needed to monitor the pressure profile, temperature profile and gas injection profile. Therefore, monitoring gas injection profile has becoming an important part of gas drive reservoirs.
Donghe Oilfield was characterized by ultra-deep (&gt;6000m), high temperature (&gt;140°C) and high content of carbon dioxide, conventional manometer and thermometer cannot meet the downhole condition of ultra-deep and high temperature. To continuously monitor gas injection well, permanent fibre-optic surveillance technique featured with outstanding conformance, nice corrosion resistance and long-life span was developed, and a program was developed to use real-time fiber-optic Distributed Temperature Sensing (DTS) and Distributed Acoustic sensing (DAS) to identify the gas injection profile (gas channeling).
Monitoring principle and system assembly of the fibre-optic was demonstrated in detail, the DTS utilized Joule - Thompson cooling principle as the gas injected into formation through screen pipe, while the DAS captured the amplitude and frequency of acoustics from the gas flow. DTS and DAS data obtained at the same time by using fiber wireline outside the gas injection string during gas injection.
There was a field application in gas injection well of DH1-H3 and gas injection profiles derived from DTS and DAS had the extremely high consistency to radioactive tracer profiles run at about the same time and under similar injection rates and pressure. The success of the fibre-optic surveillance in DH1-H3 exhibited great potential of fiber-optic sensing in gas injection EOR projects, which could provide a new and effective tool in identifying gas channeling.
Automatic Simulation Data Update: A New Innovative Way to Expedite Historical Data Extension for Models
Authors: Tayeb Yousef , Naseef Faisal , Ghamdi Amell 
Published: March 2021

Abstract
Historical data in reservoir simulation models becomes outdated with time and the gap between the latest history matched model and the current situation increases. Time is essential, especially with escalated numbers of simulation models. Therefore, updating models in a frequent manner requires a new approach to maximize human resources and deliver timely answers. Engineers must also ensure that the existing quality checked input is secured and that data integrity is maintained during updates.
In the conventional method of updating simulation model data, engineers go through several steps to acquire new data from corporate databases and fill the extended missing periods. This procedure involves interacting with many applications, which is very time-consuming. To expedite this process, a new methodology is applied that automates each of the single interactions together in a one-step procedure. A smart in-house tool connected to the corporate database extracts all necessary data and generates consistent inputs, including rates, pressures and well completions as data is developed. The tool then incorporates the new data into the existing simulation model's data input.
The smart automation tool shows the positive impact of the one-step methodology in the updating process. As an example, the new tool was tested on a mega-field, where a vast number of wells were perfectly updated and extended to the current simulation date. The updating time was drastically reduced using the indroduced process and engineers were able to keep their existing files. In addition, the smart automation tool was able to connect to the corresponding geological model seamlessly to generate the specified perforation data after incorporating all trajectory and completion data automatically.
This paper illustrates that the automation of the updating process is essential to increasing workflow efficiency. The opportunity for fast and frequent simulation model updates leads to a better understanding of reservoir behavior and improves forecasting.
Advanced Completion Optimization ACO: A Comprehensive Workflow for Flow Control Devices
Authors: Ahmed Elfeel Mohamed , Goh Gordon , Biniwale Shripad 
Published: March 2021

Abstract
There is a growing interest in downhole flow control devices (FCD) as they can be used to counter the effects of reservoir heterogeneity and improve hydrocarbon recovery. The variety of FCD types, sizes, and specifications makes it challenging to select the right device, providing an optimal investment return. Reservoir engineers play an essential role in identifying and evaluating the possible options based on numerical simulation models. This paper utilizes a transient numerical optimizer, designed for FCD with active controls, as a generic tool for lower completion optimization, including passive and autonomous FCD.
The workflow consists of five steps. The first step is to determine a practical number of completion zones in a well, given the reservoir heterogeneity and completion string considerations. The second step is to explore the potential gains of downhole control without accounting for device-specific limitations. Here, we integrate a local optimization method to run several simulations with reactive and proactive strategies. In the third step, we contrast the local optimization simulations results to determine the suitable family of FCD: passive, autonomous or active. In step four, we ensure the selected FCD family is correctly modelled in reservoir simulation, particularly for autonomous devices, based on a recently published method to calculate equipment specific flow coefficients. Finally, optimization runs are performed using the selected FCD family and specific coefficients.
The workflow is demonstrated on a synthetic carbonate sector model with a ~2,000 m horizontal well. It can be shown that analyses of the local optimization results provide quick guidelines to screen and select suitable lower completion equipment for the well and reservoir. Furthermore, the local optimization results can be used to design the selected lower completion string. The suggested workflow is the first of its kind in that it caters to all FCD families. The workflow uses an efficient local optimization method in a next-generation reservoir simulator. The efficiency gains from using the optimizer allows the decision-making time required for FCD evaluation to be an order of magnitude less than the logging and completion operation timeframe. Hence, the workflow enables efficient real-time design, planning and optimization of FCD.
The Model of Sandbody Controlled by Dynamic Provenance System and its Exploration Significance in Superposition Area of Strike-Slip and Extension Stress in the South of Bohai Sea
Authors: Zhen Huang , Bo Yang , Guoying Li , Jian Ren , Xiaoling Wang 
Published: March 2021

Abstract
Laizhouwan sag in Bohai Bay basin is a fault basin controlled by extensional fault depression and strike slip pull apart, which is an important oil and gas exploration area in Bohai Bay. Exploration practice shows that the prediction of high quality reservoir is the core problem of exploration in this area. Based on the analysis of drilling, seismic data and structural physical simulation in Laizhouwan depression, this paper analyzes the structural deformation under the stress field of strike slip extensional superposition, and points out the dynamic source controlled sand model in the strike slip extensional superposition area. Firstly, The structural response of "pressure relief settlement, pressure boosting uplift" under the mechanism of strike slip extension stress superposition stress is the root cause of block uplift drop alternation transformation. As a result, the southern slope zone of Laizhouwan depression shows the structural pattern of early uplift and late uplift in the East and early uplift and late uplift in the west, forming a "seesaw" structural evolution pattern. Secondly, the unique paleogeomorphology controls the orderly distribution of sedimentary system in time and space. In the Paleocene, the east uplifted, forming a local provenance system. In the denudation area above the slope break developed fracture weathering shell type reservoirs, and the subsidence area under the slope break developed fan delta deposits; In the early Eocene, the relatively flat platform palaeogeomorphology was developed, which created favorable conditions for the development of mixed sedimentary body of lacustrine carbonate and delta; At the end of Eocene, the West was pressurized and uplifted, the East was released and subsided, and the braided river delta sediments of Western provenance were developed. Under the guidance of this recognition, the hidden dynamic provenance was successfully identified in the study area.