bluuebunny/crossref_metadata_2025_split huggingface dataset:
DAKWAH DIGITAL UNTUK GENERASI MILENIAL : STUDI ATAS PRAKTIK DAKWAH DI KOMUNITAS OMAH NGAJI, SURAKARTA
Authors: Kristina Ayu 
Published: June 2022

AbstractTechnological progress has made the propaganda model more rapidly and dynamically developed. It is undeniable that content smells of radicalism, extremism is very quickly spread and able to enter all lines. So, the counter needs to bring fresh air like the Omah Ngaji Community. This study was conducted to find out how religion was understood and practiced by millennial generations and how da'wah was carried out in the millennial era. With a qualitative descriptive approach, through in-depth interviews of (5) informants determined based on purposive sampling the results of the study showed that religion was interpreted as a guideline for human life so as not to cause chaos. The delivery of religion in da'wah through the study of taklim, social media, and psychology emphasis to counter hate speech. That is the reason for the emergence of digital da'wah by 'ustad gaul' who are technologically literate AbstrakKemajuan teknologi mengakibatkan model dakwah semakin bekembang pesat dan dinamis. Tidak bisa dipungkiri bahwa konten-konten berbau radikalisme, ekstrimisme sangat cepat menyebar dan mampu masuk ke semua lini. Maka, perlu counter yang membawa angin segar seperti Komunitas Omah Ngaji. Studi ini dilakukan untuk mengetahui bagaimana agama dipahami dan dipraktikkan generasi milenial dan bagaimana dakwah dilakukan di era milenial. Dengan pendekatan kualitatif deskriptif, melalui wawancara mendalam (in depth interview) dari (5) informan yang ditentukan berdasarkan purposive sampling hasil studi menunjukkan bahwa agama dimaknai sebagai pedoman hidup manusia agar tidak melakukan kekacauan. Penyampaian agama dalam dakwah melalui pengajian taklim, media sosial, dan pendekatan psikologi untuk menangkal jjalan Lebencian. Icj1ah a1asan mjncj1nya daLwah digica1 o1eh ‘jscad gaj1’ yang me1eL ceLno1ogi
Mountain Growth under the Combined Effects of Paleostress and Paleoclimate: Implications from Apatite (U-Th)/He Thermochronology of Taibai Mountain, Central China
Authors: Zhang Weibin , Wang Fei , Wu Lin , Shan Jingnan , Yang Liekun , Shi Wenbei , Xu Xiwei 
Published: June 2022

Abstract
Tectonics and climate are the two competitive factors sculpturing landforms. Observations on the Earth surface are affected by signals from both tectonic and climatic agents. How to clarify these signals is a key issue. We categorize factors affecting mountain growth as horizontal (extension, compression, and transpression) and vertical (mantle upwelling and climate change) forces to evaluate the driving forces of accelerated exhumation in Taibai Mountain. Based on apatite (U-Th)/He thermochronology, we document two stages of accelerated exhumation at ca. 52-46 Ma and ca. 24-19 Ma from the age-elevation relationship, confirmed by 1D half-space modeling and QTQt inverse modeling. In the framework of paleostress, the two accelerated exhumation events occurred during transpressional periods in the early Eocene and late Oligocene-early Miocene in East China. These two events were triggered by the localized contractional deformation at the intersection of the North Qinling and Fengxian-Taibai faults: The opposite-direction shearing of these two faults was responsible for the former event with an unroofing magnitude of ~1 km; the same-direction shearing of the two faults resulted in the latter event with an unroofing magnitude of ~0.6 km. The far-field effects of both India-Eurasia collision and Pacific subduction drove the accelerated exhumation at ca. 52-46 Ma. The lateral extrusion of the Tibetan Plateau acted as the main driving force for the accelerated exhumation at ca. 24-19 Ma, which may have been slightly influenced by the intensified Asian summer monsoon in the early Miocene.
Effect of Earthquake on Pressure Arch above the Tunnel
Authors: Sun Changxin , Jiang Tong , Lv Xiaochun , Zou Mingjun 
Published: June 2022

Abstract
In this paper, the changes in the pressure arch height above the tunnels subject to earthquake were analyzed by using theoretical, numerical, and experimental ways, respectively, and then, a corresponding formula was derived. The phenomenon of stress rotation and pressure arch around the tunnel under earthquake was found by illustrating the stress vector around tunnel. The force transmission method was used to analyze the change in pressure arch height of rectangular, horseshoe-shaped, and circular tunnels before and after earthquake, and then, a new method was presented to determine the pressure arch height above the tunnel under earthquake according to stress changes in surrounding rock. Then, the two methods were jointly used to analyze the pressure arch height above the tunnel. The results show that the tunnel shape has great effect on the shape of pressure arch, and the pressure arch height of deep tunnel varies little with depth. The changes in the shape and height of tunnel pressure arch before and after earthquake obtained from theoretical analysis and numerical simulation were finally verified by shaking table model tests. The research results in this paper may provide practical significance in seismic design of tunnel structures.
An Integrated Model Combining Complex Fracture Networks and Time-Varying Data Modeling Techniques for Production Performance Analysis in Tight Reservoirs
Authors: Cao Chong , Cheng Linsong , Jia Zhihao , Jia Pin , Zhang Xuze , Xue Yongchao 
Published: June 2022

Abstract
Efficient development of tight reservoirs often relies on complex-hydraulic-fracture-network. Due to the time repeated iteration for simulation, the (semi)-analytical model or fully-numerical model often requires a trade-off especially for the accuracy of production analysis. Hence, a comprehensive model for accelerating production matching needs to be established. In this paper, a neighboring-long-short-term-memory (n-LSTM) model, integrated with a complex fracture semi-analytical flow model, can make production performance analysis with high efficiency. The interconnections between hydraulic and natural fractures with arbitrary angles and complex geometry were considered in flow model. Then, the reservoir flow derived from Laplace domain was coupled with fracture network flow numerically solved by finite difference method to obtain the semi-analytical flow solution. The specific distribution of flow solutions was obtained based on the range of reservoir properties, well information, and geological parameters. Thus datasets including production rate and date can be constructed, enlarged and split into training and testing dataset.
The integrated model proposed in this paper adopted a non-orthogonal network with 4100 feet length and 53 segments for testing, and was applied for the characterization of complex fractures in the Changqing tight reservoir in the Ordos Basin, China. It is worth mentioning that 65 semi-analytical solutions are expanded to 1280 pairs of production-time data point using the n-LSTM model. With the strong power of capture and excavate the non-linear relationship between multitype data, it only takes a few minutes to forecast and match the daily production data with samples from actual oilfield. As a result, the mean square error of 0.31% in the training dataset and 2.63% in the testing dataset shows that the semi-analytical solution that accurately characterizes the complex fracture networks can be combined with improved LSTM for the prediction and analysis of oil production. In addition, it can be found that the prediction results of the integrated model can also identify the 1/4 slope and 1/2 slope straight lines in the log/log transient response curve. The interpreted results expand the application of semi-analytical solution assisted data-driven model and reduce the consumption of a large amount of repetition time.
This paper provides an integrated data-driven model combined with semi-analytical model to make well performance analysis with more efficiency and high accuracy. This workflow, incorporated with fracture precise characterization, data generation and expansion, prediction and calibration, can be readily applied in oilfield to obtain fracture parameters with less time. In addition, time-series and small samples can be enlarged and excavated, especially for the in-proper records in production history.
Temperature Specifications for CCUS Completions Equipment: Steady-State and Transient Thermal Simulations
Authors: Vasper Adam C , Fagereng Ingvild Bakke 
Published: June 2022

Abstract
Different simulated injection scenarios can significantly cool carbon capture utilization and storage (CCUS)wells. Cases representing different scenarios were modeled to help determine appropriate temperature specifications for completions equipment in CCUS wells.
Depleted reservoirs, in particular gas reservoirs, will not support a static column of liquid or dense-phase CO2 to surface at the initial reservoir pressure. During injection, unless there is significant friction or backpressure, the upper part of the well will be at low pressure, with CO2 in the gas phase. Injected, liquid CO2 will depressurize across the wellhead choke, or the upper tubing, resulting in significant cooling as the saturation curve is reached and the CO2 starts flashing. For steady-state injection across a narrow range of rates, a tapered or narrow completion string can be designed that provides sufficient friction pressure to keep the CO2 in the liquid phase. A portfolio or set of wells, potentially with different tubing sizes, will give more flexibility for managing injection rates.
Transient scenarios such as injection startup or shutdown cause rapid changes in rate and can consequently induce severe thermal shocks. These cannot be completely prevented using only friction or passive downhole devices. Many completion options have been proposed to provide flexibility for injection rate changes and/or reservoir pressure increases. These include concentric or dual strings providing multiple flow paths with different flow areas and hence friction, downhole passive chokes, backpressure control valves, surface-operated downhole flow control valves, and various combinations of these and other technologies. Currently, the only methods to eliminate all the scenarios consideredmay be (active) backpressure control and surface-controlled downhole flow control valves. Whereas the transient effects are most severe in depleted reservoirs, they are also shown to occur in reservoirs approaching hydrostatic pressure.
The most important component in the completion string is arguably the subsurface safety valve (SSSV). API 14B specifies a maximum leak rate for the closed SSSV. Following a blowout or depressurization event, a leak of high-pressure, liquid CO2 from below the SSSV to low-pressure, gas-phase CO2 above will cause localized cooling at the SSSV, in addition to that caused by the initial depressurization condition. Modeling included simulations of blowout and subsequent SSSV leakage phases for different periods of injection and hence reservoir cooldown.
To quantify these effects, the work considered temperatures in the different radial sections of the well versus time and depth. Sensitivities on annulus fluid, reservoir properties including pressure and permeability, the rate of mass transfer between phases, and other variables were also investigated. Modeling was performed using a commercial dynamic multiphase flow simulator.
Model for Predicting Wellbore Temperature and Pressure in Offshore CO2 Storage Wells and the Influencing Factors
Authors: Ma Weizhen , Guan Zhichuan , Yan Yan , Li Cheng 
Published: June 2022

Abstract
The CO2 physical parameters are greatly influenced by the wellbore temperature and pressure during the offshore burial process, but the existing model does not take this into account resulting in poor calculation accuracy, which brings large errors to the later wellbore load calculation and wellbore integrity evaluation. Based on heat transfer and other basic theories, a wellbore temperature and pressure calculation model was established. the calculation method of CO2 physical parameters required for the model was determined, and finally the established model was solved by iterative calculations to obtain the temperature and pressure distribution of the wellbore and the change law of physical parameters, and the effect of injection parameters on the wellbore temperature and pressure was analyzed. Taking a buried well in the South China Sea as an example, the analysis found that as the well depth increased, the wellbore temperature and pressure increased approximately linearly, and constant pressure specific heat capacity, Nusselt number and convective heat transfer coefficient of CO2 fluid increased, while the density, viscosity, friction coefficient, thermal conductivity and Prandtl number decreased. An increase in injection temperature decreases the temperature gradient, but has little effect on the pressure gradient and bottomhole temperature and pressure; an increase in injection volume decreases the temperature gradient and increases the pressure gradient, and the bottomhole temperature can be effectively regulated by the injection volume; the injection pressure has a certain effect on the temperature gradient at low pressure, but has a most no effect on the pressure gradient, and the bottomhole pressure can be effectively regulated by the injection pressure.
Limitations of Commercial Software in Estimating Trapped Gas Saturation and Hysteresis in Relative Permeability
Authors: Aghabozorgi Shokoufeh , Sohrabi Mehran 
Published: June 2022

Abstract
Permanent storage of carbon dioxide requires accurate estimation of trapped gas saturation and reservoir storage capacity. Hydrogen and gas storage in subsurface reservoirs involves injection and withdrawal cycles, which necessitates the accurate estimation of hysteresis in relative permeability (kr) and capillary pressure (Pc) data. Cyclic injections in the form of Water Alternating Gas (WAG) injection is an effective Enhanced Oil Recovery (EOR) method for improving volumetric sweep efficiency in the reservoirs. When simulating all these processes, subsurface reservoir engineers rely on commercial software to estimate trapped gas saturation and cyclic hysteresis in kr and Pc data. However, few researchers have investigated the reliability of the available hysteresis models implemented in commercial software for this purpose.
To this aim, a thorough sensitivity analysis was performed to investigate the performance of three-phase hysteresis models available in the literature for simulating the measured data of cyclic experiments. The Water Alternating Gas (WAG) experiment used in this study was performed at near-miscible conditions on a mixed-wet sandstone sample, and the cyclic injection was started with drainage.
The results show that when simulating WAG experiments performed at low injection rates, using a hysteresis model developed by Aghabozorgi and Sohrabi (2019) provides the most accurate results for pressure drop, fluid saturations, and gradual oil production. However, the model developed by Larsen and Skauge (1998) can be only used for experiments reaching maximum gas saturation in their first three-phase imbibition cycle, mostly representing the limited grid blocks near the wellbore. Even in this scenario, the dependence of the model on Land’s initial-residual relationship and trapping coefficient is questionable.
This study highlights the possible pitfalls of using commercial software for estimating trapped saturation and hysteresis in relative permeability and capillary pressure. It also provides useful suggestions for improving the accuracy of performed simulations. The presented results are vital for the oil and gas experts as they can demand improvements in current approaches and promote constant growth and development of commercial software.
Application of Bag-of-Features Approach to Drilling Accidents Forecasting
Authors: Gurina Ekaterina , Klyuchnikov Nikita , Antipova Ksenia , Koroteev Dmitry 
Published: June 2022

Abstract
A significant proportion of capital and operational expenditures of oil and gas companies falls on the well construction. Unexpected situations inevitably happen during drilling regardless of the well's construction technology level and available information. These situations lead to more spending and noon-productive time. We present a machine learning (ML) algorithm for predicting accidents such as stuck, mud loss, and fluid show as the most common accidents in the industry.
The model for forecasting the drilling accidents is based on the Bag-of-features approach, which implies labeling segments of surface telemetry data by the particular symbol, named codeword, from the defined codebook. Building histograms of symbols for the one-hour telemetry interval, one could use the histogram as an input for the machine learning algorithm. For the ML model training, we use data from more than 100 drilling accidents from different oil and gas wells, where we defined more than 3000 drilling accident predecessors and about 5000 normal drilling segments.
Model performance was estimated using two major metrics.The coveragemetric, indicates the ratio of true forecasted events. Number of false alarms per day metricfor the specified probability threshold. Using different schemes of metric calculation, one could evaluate the model's ability to both forecast and detect accidents. Validation tests justify that our algorithm performs well on historical and real-time data. At each moment, the model analyzes the real-time data for the last hour and provides the probability of whether the segments contain the signs of drilling accident predecessors of a particular type. The prediction quality does not vary from field to field, so the ML model can be used in different fields without additional training.
Nowadays model is tested in real oilfields in Russia. To operate the model, we developed software integrated with the Wellsite Information Transfer Standard Markup Language (WITSML) data server into clients' existing IT infrastructure. All calculations arein the cloud anddo not require significant additional computing power on client side.
Should We Care About the Background Gas Effect on Reservoir Properties Prediction Using Machine Learning and Advanced Mud Gas Data?
Authors: Anifowose Fatai Adesina , Mezghani Mokhles Mustapha , Badawood Saleh Mohammed , Ismail Javid 
Published: June 2022

Abstract
Background gas is the baseline gas measurement due to the recycled gas dissolved in or expelled from the drilling mud additives. It occurs more in oil-based mud systems than in water-based. A cut-off is usually applied on the mud gas data to remove the background gas effect in traditional mud gas analyses. This imposes an overhead on modeling procedures. This study investigates the effect of applying the cut-off on the performance of machine learning algorithms.
A case of porosity prediction using advanced mud gas data is considered in this study. Using data from six wells, we implemented two experiments to compare the performance of artificial neural networks (ANN) with and without the cut-off. The first experiment applies a cut-off of 100 ppm on the total normalized gas while the second uses the entire data without the cut-off. The comparative results are benchmarked with those of a multivariate linear regression (MLR). Each well dataset was split into training and validation subsets using a randomized sampling approach in the ratio of 70:30.
The results compare each of the MLR and ANN models individually and over all the datasets without and with the cut-off applied. The ANN models show better or same performance on the datasets without the cut-off in four out of six cases (67%). This shows that the ANN models may be less affected by the presence of the background gases in the mud gas datasets. It could be preliminarily concluded, based on the data used in this study, that it might be unnecessary to apply cut-offs on the mud gas data for ML algorithms due to their capability to handle noisy data. This conclusion is, however, subject to more extensive studies while ensuring consistency. Avoiding the application of the cut-off will remove the unnecessary overhead and provide more data for effective ML model training.
While the results of this preliminary study somewhat agree with the traditional practice of applying a cut-off on advanced mud gas data, more extensive experiments will be conducted in our future work to further validate the conclusion. The background gas is traditionally considered noisy. In ML modeling, it could provide more information to further explain the nonlinear relationship between the input features and the target variable, hence improving the predictive capability.
Investigation and Simulation of SWAG injections Performed in Mixed-Wet Carbonate Rocks.
Authors: Alnuaimi Latifa Obaid , Aghabozorgi Shokoufeh , Sohrabi Mehran 
Published: June 2022

Abstract
The average recovery factor of current producing oil reservoirs is about 35-50% worldwide. Enhanced Oil Recovery (EOR) methods such as Water Alternating Gas (WAG) target the oil left in place and improve the final recovery of the developed fields. In a WAG injection plan, some reservoir blocks experience simultaneous gas and water flow. Therefore, Simultaneous Water And Gas (SWAG) injection experiments are performed to understand and simulate the fluid flow behaviour in these blocks more accurately.
The experimental data we analyzed in this manuscript were obtained by performing a SWAG experiment using real reservoir rock and fluid (mixed-wet carbonate rock extracted from the Abu-Dhabi field). In miscible and immiscible experiments, the injected gas was Methane and CO2, respectively. We tried to simulate the experiments using Stone's, Baker's, and Stone's exponent models to evaluate the performance of these models in simulating SWAG experiments. It was shown that SWAG displacement can be simulated using Stone's first model and changing two-phase kr data as a matching parameter. The results showed that we do not need to correct the three-phase relative permeability in the low oil saturation region for simulating SWAG experiments.
The study presented in this paper is novel in two aspects: first, the SWAG experiments were conducted in reservoir carbonate samples using real reservoir fluids; and second, even though many researchers have simulated the WAG experiments, not many have discussed the simulation of SWAG experiments. The results presented in this paper is of utmost importance for decision making, designing, and simulating CO2-EOR plans in giant Abu-Dhabi carbonate reservoirs.