bluuebunny/crossref_metadata_2025 huggingface dataset:
The Solution to the Cosmological Constant Problem
Authors: Craig Brian
Published: November 2019

To account for the very low mass density associated with Dark Energy and the Cosmological Constant, a new approach to the ground state of empty space is presented. The resulting model for the vacuum state associated with empty space proposes a crystalline-like texture for the chromatic structure of empty space. This vacuum state has the appropriate mass density and predicts acceleration for the Universe expansion. Furthermore, the model predicts that this texture is anisotropic and may lead to measurable changes in the production of electron and positron pairs by gamma rays incident on a solid crystal of low mass density such as graphite.
Highly Efficient, ITO-Free Polymer Solar Cells Using Ultrathin Copper Film as Transparent Electrode
Authors: Liang Quanbin , Luo Guoping , Cheng Xiaoping , Wu Hongbin
Published: November 2019

Here we report highly efficient, indium tin oxide (ITO)-free polymer solar cells (PSCs) with an ultrathin copper (Cu) film(~10 nm) coated with a thin layer of poly[(9,9-bis(3‘-(N,N-dimethylamino)propyl)-2,7-fluorene)-alt-2,7-(9,9-dioctylfluorene)] (PFN) as transparent electrode. Despite of its lower far-field transmittance of the electrode, the obtained ITO-free device based on the ultrathin Cu film can delivery higher absorption efficiency than that of the device based on ITO substrate in the long wavelength region, which can be attributed to the formation of metal resonant microcavity between the opaque back metal mirror (MoO3/Al electrode) and the transparent Cu film with high reflectance. As a result, polymer solar cells based on poly[[2,6'-4,8-di(5-ethylhexylthienyl)benzo[1,2-b;3,3-b]dithiophene][3-fluoro-2[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophenediyl]] (PTB7-Th) and [6,6]-phenyl C71-butyric acid methyl ester (PC71BM) blend show a high power conversion efficiency (PCE) of 8.21 %, comparable to that of the control device based on ITO electrode (with a PCE of 9.60% ). The results demonstrate that thermally evaporated Cu thin film electrode can be promising candidate to replace ITO for highly efficient PSCs, thus may open up the possibility for massive production of PSCs with low cost.
Optimal Operation Strategy of ESS for EV Charging Infrastructure for Voltage Stabilization in Secondary Feeder of Distribution System
Authors: Kim Dae-Jin , Ryu Kyung-Sang , Ko Hee-Sang , Kim Byungki
Published: November 2019

The introduction of electrical vehicle charging infrastructure including EV charger, renewable energy resource at secondary feeder in distribution system has been increased as one of countermeasure for global environmental issues. However, the Electric Vehicle Charging (EVC) infrastructure may act as the peak load in distribution system, which can adversely impact on the voltage stability when the electric vehicle is quickly charged. Therefore, to keep within the limit capacity of secondary feeder and allowable limit for feeder voltage, this paper proposes a stabilization method by the Energy Storage System (ESS) control strategy at secondary feeder in order to be not violated over than lower and upper limit. Also, this paper presents the estimation method to keep the proper standard value of State of Charge (SOC). From the simulation results, the voltage stabilization operation by ESS should make the feeder voltages of the distribution system(secondary feeder) introduced EVC Infra keep better voltage conditions, also estimation method to keep the proper standard value is confirmed that the SOC of ESS when is the standby condition could be exactly kept within the proper reference range.
Efficiency Evaluation and Comparative Study of Regional Wind Power Industry in China Based on CO2 Emission Reduction
Authors: Fangrong Ren , Ze Tian , Qinwen Xiao , Lin Tai-Yu
Published: November 2019

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.
STUDI PENGAWETAN LARUTAN ENZIM BROMELIN KASAR SECARA FILTRASI DAN PENAMBAHAN NATRIUM BENZOAT
Authors: Sukendar Nandi K , Laga Amran , Siade Try Permata
Published: November 2019

(Ananas comosus (L) Merr) is a plant that contains enzyme bromelin in the fruit, leaf and skin but more in the stem. In general, enzymes are produced and marketed in powder form. However, producing enzymes in powder form requires high process technology and very expensive cost. The purpose of this research were to know how to prepare bromelin enzyme in liquid form and it preservation technique, and to know the quality of bromelin enzyme during storage. This research was conducted through 3 stages: 1. Extraction of bromelin from pineapple stem, 2. Physical and Chemical preservation and 3. Observation of enzyme storage. The results of the study showed that preservation of enzyme bromelin physically and chemically still performed enzyme activity on day 32, while enzyme without preservation did not show activity at day 24. Bromelin enzyme with physical preservation was better than chemical preservation.
STUDI PEMANFAATAN DAUN SIRSAK (Annona murica linn.) SEBAGAI MINUMAN SEDUH DENGAN PENAMBAHAN TEH (Camelia sinensis) SEBAGAI MINUMAN FUNGSIONAL
Authors: Tahir Mulyati M. , Langkong Jumriah , Anmar Anmar
Published: November 2019

Kepok banana (Musaparadisiaca formatypica) is one fruit that contains enough digestivefiber for the body. Kepok banana (Musaparadisiaca formatypica) is usually processed byfrying or steaming, bananas have a short shelf life and easily damaged. Therefore, to extendthe shelf life of bananas, fruit will be processed into fruit leather products. However, becausethe color of bananas are less attractive, the color addition will make the product preferred byconsumers. Terung belanda (Solanum betaceum cav. has a bright color and has enough fibercontent so well processed into fruit leather. The objective of this research was to find the besttreatment combination between kepok banana (Musaparadisiaca formatypica) and terungbelanda (Solanum betaceum cav.) sugar concentration to produce a good physical andchemical properties and favored by consumers. The research was also to find out the effect ofsugar concentration addition to physical, chemical and organoleptic fruit leather banana andterung belanda (Solanum betaceum cav.). Treatment applied was A1: kepok banana(Musaparadisiaca formatypica) mashed 50%: terung belanda ((Solanum betaceum cav)mashed 45%: sugar 5%; A2: 45%: 40%: 15%; A3: 40%: 35%: 25%. Fruit leather is then testedorganoleptically including color, flavor, taste and texture and was chemically tested including moisture content, total acid, pH, anthocyanin and fiber. The result of the research shows thatA1 treatment: 50% banana porridge: terung belanda porridge 45%: 5% sugar produces thebest fruit leather product in terms of water content, total acid, pH, anthocyanin, fiber, aroma,taste, and texture
Construction of Chinese University Culture from the Perspective of Multimodal Metaphor and Metonymy—A Case Study on the 2018 Admissions Film ‘Graduation Answers’ of Tsinghua University
Authors: Huan Jin , Youguo Duan
Published: November 2019

The admissions films of the university are an important way to show their culture to the outside world, which is a typical multimodal discourse. By analyzing the construction of university culture in the “Graduation Answers” from the perspective of multimodal metaphor and metonymy, it is found that there are multi-modal metaphors such as images and words, gestures and words, music and words, and metonymies such as individual representing entirety and clothing representing identity in the admission film, which enhance the expressive power of the video and resonate with the audience.
Effect of Live-Crude-Oil Composition on Optimal Salinity of a Surfactant Formulation: Experiments and Modeling
Authors: Marliere Claire , Creton Benoit
Published: November 2019

The objective of aqueous-surfactant formulation design is to achieve ultralow interfacial tension (IFT) with the oil in place at reservoir conditions. Several parameters have to be investigated, and among them, it is well-known that the presence of gas dissolved in crude oil can greatly affect the surfactant/brine/crude-oil-microemulsion phase behavior. Omitting it might degrade the formulation performance. In this work, we present a combined experimental and theoretical investigation of optimal-salinity evolution as a function of live-oil compositions and conditions, varying the pressure independently of the gas/oil ratio (GOR) (i.e., the amount of gas dissolved in crude oil).

A specific high-pressure/high-temperature (HP/HT) sapphire cell with a mobile piston is used to separately study the effect on the optimal salinity of the GOR by adding different amounts of n-alkanes methane (C1), ethane (C2), and propane (C3) at the corresponding saturation pressure, and the effect of pressure (up to 500 bar) is studied in a second cell by varying the cell volume (without changing the live-crude-oil composition).

Using the HP/HT sapphire cell, we show that GOR variations (tested values up to 135 std m3/m3) induce important modifications of the brine/surfactant/oil-microemulsion phase behavior. In the case of the studied fluids, experimental data indicate that the optimal salinity of the brine/surfactant/oil system decreases linearly when increasing the amount of gas dissolved in the live crude oil. As a consequence of the Salager relation (Salager et al. 1979), the equivalent alkane carbon number (EACN) of the live crude oil varies linearly with the GOR. We demonstrate hereafter that the cell pressure alone (up to 500 bar), for a fixed composition (i.e., fixed GOR), affects neither the formation nor the stability of the Winsor III (WIII) microemulsion. Furthermore, results suggest that the composition of the dissolved representative gas can have an effect on the microemulsion phase behavior.

Three models have been evaluated to estimate EACN values for 13 live crude oils and for the two live oils of interest in this study [Crude Oil 1 and n-tetradecane (n-C14)]. We compared predictions with our new experimental data. The Creton and Mougin (2016) model quantitatively predicts the behavior of live oils and agrees with the negligible effect of pressure on microemulsion formation and stability.
An Algorithm for Automated Identification of Waterflood Pattern Elements
Authors: Ignatov Ivan
Published: November 2019

For waterflood management and production optimization purposes, producers and injectors are often grouped into pattern elements based purely on the wells' location. This grouping is often done manually and can be time consuming. Also, for irregular patterns is it not always obvious which wells can be grouped together. The paper presents an algorithm that formalizes the grouping and automatically identifies pattern elements.

The presented algorithm focuses on identification of pattern elements that contain one producer and several neighboring injectors. First, using the wells' coordinates as input data, Voronoi polygons are constructed. Based on the well types (producer or injector) and common edges of Voronoi polygons producer-injector pairs are identified. Pattern elements are constructed by splitting Voronoi polygons of injectors and adding their parts to Voronoi polygons of producers from correspondent wells pairs. In the resulting pattern elements injectors are located in one of the vertices while producers lie inside the element.

The presented algorithm was tested on synthetic examples and proved to identify pattern elements for both regular (e.g. line drive, 5-spot, etc.) and irregular waterflood patterns. Therefore, it is suitable for automated analysis of waterflood patterns in cases where data or time constraints do not allow to implement streamline analysis or other sophisticated techniques. Calculation of voidage replacement for each identified pattern element allows to reveal areas of over-injection as well as areas lacking pressure support, and accordingly adjust rate targets for each injector in order to achieve and maintain a balanced waterflood. Automated identification of waterflood pattern elements helps to timely adjust water injection when new producers come on stream or existing wells shut-in.

The proposed method provides a fast and pragmatic approach of identifying and updating patterns without performing dynamic simulation. Formalized steps of the presented algorithm allow automated identification of waterflood pattern elements. In addition to manual labor savings, it avoids subjectivity and ambiguity that can arise in case of irregular patterns.
Kuwait's First Memory Production Logging in Horizontal Section Conveyed with Normal Coiled Tubing, Challenges, Risk Assessment and Solution
Authors: Almohammad Humoud , Ayyad Hazim , Sultan Alaa , Rane Nitin , Abdulrahim Khaled , Bumajdad Mohammed , Mehraj Majid , Al-Hamdan Abdulaziz , Al-Mutairi Norah , Al-Khamis Abdulaziz , Al-Derbass Abdullah
Published: November 2019

Studying the flow behavior in horizontal section addresses further challenges and complexity. Innovative technologies were developed to overcome the fluid segregation challenges in horizontal sections and cover the entire production profile. In Kuwait, horizontal production logging is typically conveyed on 1.75" electrical coiled tubing which is relatively large size and therefore increases the risk of choking the well or killing low flowrate wells. Also, there is a limitation on the availability of the electrical coiled tubing.

Greater Burgan smart ICD wells require a periodic assessment of the production profile and the contribution from each port to overcome the increasing water cut challenge in such a mature field. To identify the source of water, the engineers planned a new strategy to minimize the choking effect through use of smaller coiled tubing size. However, the available small size coiled tubing are not equipped with an electrical line for real-time data streaming. This challenge was resolved by opting for a horizontal PLT logging recording in a memory mode acquisition.

Running the production logging in memory mode is not unusual in vertical and slightly deviated wells, but it is not common in horizontal wells. Risk assessment was carried out trying to eliminate all the expected obstruction such as having a dummy run while monitoring production behavior on the surface using a testing unit, reducing the coiled tubing speed to avoid disturbing the flow stabilization and watching for any indication of coiled tubing tension-compression changes. A contingency plan was in place, for carrying out a nitrogen activation in case the well chocked below the accurate reading limits during the logging. Following the detailed steps and extensive planned procedure, the logging with memory mode in the horizontal section was successful and resulted in accurate flow profile determination along with contribution from each ICD ports. Using normal coiled tubing instead of the electrical coiled tubing has resulted in reduced operational cost and eliminate the challenge of the limited availability of electrical coiled tubing that was delaying the PLT jobs. The major production logging output was accurately presented from the memory mode.

This paper includes the challenges from using memory production logging in horizontal section. A risk assessment for each of the challenges and contingency plan to apply this method.
From HAZOP Automation to Intelligent Real-Time Operator Decision Support by Means of Multilevel Flow Modelling
Authors: Myllerup Claus Marner , Wu Jing , Zhang Xinxin , Lind Morten
Published: November 2019

For decades, efforts have been made to automate the HAZOP process. The motivation has mainly been to displace expensive manual HAZOP approaches, that are furthermore known to suffer from systemic quality issues related to system complexity, uncertainty, vagueness and level of knowledge completeness.

With offset in a review of the main historic arguments for automating the HAZOP analysis, and an outline of the particular benefits of employing Multilevel Flow Modelling (MFM) theory in this context, this paper emphasises the opportunity to redeploy the insights achieved by the HAZOP team to assist an operator facing an abnormal event years later.

By means of a detailed analysis of an actual catastrophic failure of a FPSO compression module, the paper demonstrates how MFM enabled HAZOP captures explicitly tacit expert knowledge about the complex interdependencies between process design, equipment design, safety barriers and instrumentation. The paper further describes a methodology to interpret measurements online by means of the MFM analysis, thereby establishing real-time cause and consequence analysis in sufficient time to interrupt the escalation from a benign sensor malfunction to a topside explosion.

The paper concludes by outlining a knowledge management framework centred in MFM of the technical, operational and organizational safety barriers, which would make hitherto tacit knowledge explicitly available at all critical decision points during the lifecycle of a process plant, from design and HAZOP to commissioning, operation and decommissioning, as well as in any plant modification required along the way.

The MFM theory was adapted and extended to capture the experienced failure mode and thereby facilitate HAZOP automation and subsequent intelligent real-time operator decision support.
Exploration and Production: Reducing Geological Risk in the Middle East
Authors: Cousins Thomas , Davies Roger , Gravestock Chris , Jewell Thomas , Simmons Mike , Sutcliffe Owen
Published: November 2019

Exploration in the Middle East can benefit from the creation of sequence stratigraphy-based, scalable, 3D models of the subsurface that are, in effect, a subsurface digital twin that extends from the plate to pore. Stratigraphic and structural organization are integrated into this model to provide a predictive geological framework for analysis of reservoir- and regional-scale geology. This framework enables testing of novel geologic concepts on the Arabian Plate.

The first step of model design is to temporally constrain data within a sequence stratigraphic framework. Publically available data were used in the entire construction of this model. This framework enables the generation of plate-wide chronostratigraphic charts and gross depositional environment (GDE) maps that help to define major changes in the regional geological context. The integration of a geodynamic plate model also provides deeper insight into these spatial and temporal changes in geology. The subsurface model also adopts the principles of Earth systems science to provide insight into the nature of paleoclimate and its potential effect on enhancing the predictive capabilities of the subsurface model. A set of plate-scale regional depth frameworks can be constructed. These, when integrated with GDE maps and other stratigraphic data, facilitate basin screening and play risking.

This plate to play methodology has yielded value through the development of new play concepts and ideas across the Arabian Plate. Exploration has historically relied on the identification of large structures. However, the majority of these are now being exploited. Underexplored stratigraphic traps, and unconventional resources are new concepts that can be better evaluated by using a digital twin of the subsurface. The integration of seismic data and sequence-stratigraphy-calibrated wireline log data can be used to identify the subcrop pattern beneath an unconformity, as well as regions where potential reservoir rocks are in juxtaposition with seals. Intrashelf basins are a key feature of the Arabian Plate. They lead to stratigraphic complexity, yet are key factors for both source rock and reservoir development. From an unconventional perspective, novel, tight plays that exist within or above prominent source rock intervals can also be established.

Value and insight into previously underexplored play concepts, such as within the Silurian Qusaiba Member and the Cretaceous Shilaif Formation of Abu Dhabi, can thus be generated from the stratigraphic attribution of geoscience data. This data can enable better-informed predictions into "white space" away from data control.
Real Time Stuck Pipe Prediction by Using a Combination of Physics-Based Model and Data Analytics Approach
Authors: Zhang Feifei , Islam Aminul , Zeng Hao , Chen Zengwei , Zeng Yijin , Wang Xi , Li Siyang
Published: November 2019

Nearly one third of the drilling time lost is caused by stuck drill pipe. In many cases, stuck pipe is preventable if early signs are detected and timely measures are taken, particularly for stuck pipe events caused by solids (primarily drilled cuttings) in the wellbore. This paper presents a physics-based model and data analytics combined approach to predict stuck pipe caused during drilling.

The new proposed method combines the physics-based first principle models, including transient solid transport model, drill string model (torque and drag model) and the data-driven models. The proposed models will be worked based on the analysis of both field and experimental data. The physics-based models capture the basic rules of fluid mechanics, drill string mechanics, and multiphase flow during the drilling operations.

By analyzing field data from historical wells and experimental data, an EnKF based data-driven model is applied to provide parameters and coefficients needed by the physics-based models. The data-driven model improves the reliability of the results predicted by the first-principle based model and allows it to continuously improve itself.

Based on a transient approach, this development can use real-time drilling operational data as inputs, predict the stuck pipe risks, and provide warnings when a high risk for stuck pipe scenarios are encountered. Comparing to existing stuck pipe prediction approaches, the new proposed approach can distinguish the hole cleaning related stuck pipe risk and other reasons to create stuck pipe. This hybrid method in build technology will use as a supporting tool in decision make. Resulting to bring an opportunity for the drillers to avoid the potential stuck pipe incidents by taking a proper action in time.
Acid Gas Removal Unit Successful Switch from Silicon to Polyglycol Antifoam to Eliminate Foaming
Authors: Al Rumaih Mohammed
Published: November 2019

Natural Gas Liquefaction (NGL) plant Acid Gas Removal (AGR) unit successfully switched from silicon based to polyglycol based antifoam. Changing the type of antifoam was to eliminate the repetitive foaming occurrences in the AGR amine absorber, and to avoid the side effects of the excessive silicon deposits in the circulated amine. The polyglycol based antifoam was found to be more effective and required at lower concentration.

The AGR unit experienced repetitive amine absorber foaming since the plant commissioning. The foaming events are due to feed quality challenges in the form of liquid hydrocarbon carryover, and suspended solids entrainment. The repetitive foaming led to frequently disturbing the plant operation, reducing the unit throughput and impacting the product quality. To decrease the foaming occurrences the mode of operation for the antifoam injection was changed from intermittent injection to continues injection. However, the unit was so sensitive to the antifoam flow interruptions.

The required concentration of the silicon based antifoam was high (110 – 130 PPM compared to 20-25 PPM for the polyglycol based antifoam). This led to the side effects of the excessive silicon deposits in the system, such as the fouling of heating equipment (heat exchangers, reboilers and air coolers), the frequent amine filters clogging, and increasing the circulated amine total suspended solids.

The main objective for switching the type of antifoam is to eliminate the foaming events while minimizing the side effects of the silicon deposits. The polyglycol based antifoam was found more effective for continuous injection with concentration of 20-25 PPM. Furthermore, in the case of minor foaming in the amine absorber, increasing the antifoam concentration to 500 PPM was found to be effective in stabilizing the absorber foaming in less than 5 minutes. In addition, the minor antifoam flow interruptions did not result in foaming events unlike the silicon antifoam.
Alternative Method to Horner's Approximation for Multirate Analysis of Pressure Buildup
Authors: Useche Marcos , Franco Francy
Published: November 2019

This paper presents a method to calculate an equivalent production rate and time (tp), that models the transient effect of a multirate production period prior to a buildup test. The proposed solution increases the accuracy of Pressure Transient Analysis (PTA).

The traditional Horner method estimates the production time (tp) using the cumulative production and the last production rate; however, this method is an intuitive but not rigorous solution that puts emphasis on the most recent nonzero production rate. There are currently commercial applications that consider the superposition effects of complex production history for PTA analysis, nevertheless, superposition can include a material balance error. The proposed technique is an alternative to superposition that uses the transient effect generated for each production period to estimate the equivalent rate and production time.

A reservoir simulation model with known petrophysical parameters, fluid properties, pressure, and temperature, is used as a reference to evaluate the accuracy of the proposed method. The studied reservoir produces through a well that uses a multirate schedule that includes two different scenarios: (1) a progressive increase in each new production rate and (2) a progressive decrease in each new production rate. Then, the well is shut-in, starting a buildup pressure response. Production time and rate are estimated by applying the Horner's approximation and the proposed solution. Finally, the results from both methods are compared with the known parameters of the reference model.

The proposed method provides a more accurate solution to buildup analysis compared to the Horner time approximation by using the production rate history. The approach can also be applied to drawdown analysis and pressure derivative analysis, keeping the precision of the calculations.
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
Authors: Abbas Ahmed K. , Assi Amel H. , Abbas Hayder , Almubarak Haidar , Al Saba Mortadha
Published: November 2019

The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the modeling part, a one-dimension mechanical earth model (1D MEM) parameters, drilling fluid properties, and rig- and bit-related parameters, were included as inputs. The optimizing process was then performed to propose the optimum drilling parameters to select the drilling bit that provides the maximum possible ROP. To achieve this, the corresponding mathematical function of the ANNs model was implemented in a procedure using the genetic algorithm (GA) to obtain operating parameters that lead to maximum ROP. The output will propose an optimal bit selection that provides the maximum ROP along with the best drilling parameters. The statistical analysis of the predicted bit types and optimum drilling parameters comparing the actual flied measured values showed a low root mean square error (RMSE), low average absolute percentage error (AAPE), and high correction coefficient (R2). The proposed methodology provides drilling engineers with more choices to determine the best-case scenario for planning and/or drilling future wells. Meanwhile, the newly developed model can be used in optimizing the drilling parameters, maximizing ROP, estimating the drilling time, and eventually reducing the total field development expenses.
Carbonate Lithology Identification with Machine Learning
Authors: Nanjo Takashi , Tanaka Satoru
Published: November 2019

Machine learning has attracted the attention of geoscientists over the years. In particular, image analysis via machine learning has promise for application to exploration and production technologies. Demands have grown for the automation of carbonate lithology identification to shorten the delivery time of work and to enable unspecialized engineers to conduct it. The image analysis of carbonate thin sections is time consuming and requires expert knowledge of carbonate sedimentology. In this study, the authors propose an image analysis technique based on deep neural network for carbonate lithology identification of a thin section, which is an important image analysis process required for oil and gas exploration. In addition, the authors consider that porosity and permeability variations in the same facies are controlled by the grain, cement, pore, and limemud contents. If the contents are accurately measured, the porosity and permeability can be determined more accurately than by using traditional methods such as point counting. The elucidation of the complex relation of porosity and permeability is the objective of automation of carbonate lithology identification. To perform image analysis of the thin section, the authors prepared a data set mainly comprising pictures of the Pleistocene Ryukyu Group, which were composed of reef complex deposits distributed in southern Japan. The data set contains 306 thin section pictures and annotation data labeled by a carbonate sedimentologist. The rock components was divided into four types (grain, cement, pore, and limemud). A convolution neural network (CNN) was utilized to train the model. After training the neural network, each of the four categories was interpreted by the trained model automatically. Resultantly, the accuracy of automatic Dunham classification was 90.6% and the mean average test accuracy of category identification was 83.9%. The interpretation seems highly consistent between human vision and machine vision in both the overview and pixelwise scales. This result indicates that it has sufficient potential to assist geologists and become a basic tool for practical applications. However, the accuracy of category identification is still insufficient. The authors believe that the model requires higher quality supervised data and a greater number of supervised data.
Unconventional Oil - Decline Permeability Multipliers for Model Calibration
Authors: Li James , Fan Li , Zhang Xu
Published: November 2019

The unconventional fracture model (UFM) has been routinely used to model complex fracture systems. The UFM generates both geometry and conductivity of simulated hydraulic fracture networks, which can be used to create unstructured grids for production simulation. The production simulation model generated from the UFM must be calibrated with actual production data so that it can be used for production predictions and different sensitivity analyses such as well spacing, landing point evaluation and completion optimization.

The calibration of the production simulation model is done by specifying oil production rate and history matching the bottomhole pressure (BHP), gas-oil ratio (GOR), and water cut (WCT) measured from oil production wells. The history-matching process mainly involves modifications of the geometry (height and length) and conductivity (permeability) of the hydraulic fracture system, as well as the stimulated reservoir volume (microfractures) surrounding the hydraulic fractures. Modification of the hydraulic fracture geometry usually requires rerunning of the UFM modeling process, which is time consuming. The modification of the hydraulic fracture conductivity usually requires the use of different permeability multipliers in different fracture regions that are defined arbitrarily. To make these modifications, a consistent and systematic process, a permeability multiplier function, has been developed and successfully used in different projects. The function and its application will be introduced and discussed in this paper.

The decline permeability multiplier (DPM) function is defined with three parameters: the permeability multiplier at the initiation point (wellbore) of the fracture, the permeability multiplier at the endpoint (tip) of the fracture, and the curvature of the decline between the two points. By adjusting these three parameters, pressure and production data (BHP, GOR, and WCT) can be reasonably history matched. In practice, the function can be applied to hydraulic fractures and microfractures separately with different parameter values. The function can be used not only to define conductivity distribution inside hydraulic fractures, but also to help initialize water saturation distributions in hydraulic fractures in either structured grids or unstructured grids. An example of water saturation distributed with this decline function to better match the water cut is also presented in the paper.
Bridging Compressor and Expander Technologies in SSLNG Processes
Authors: Drewes Michael , Patel Tushar
Published: November 2019

Today, small-scale liquified natural gas (SSLNG) plants are planned and built in different areas around the globe. Due to the overall market situation and competition, these projects are challenged to decrease capital expenditure (CAPEX), while becoming increasingly efficient to meet mid-size investors' operating expenditure (OPEX) targets and return on investment (ROI) expectations. The main challenges are the overall efficiency of the plant, seal leakage rates, operational flexibility and the plant's space limitations.

To a big extent, the aforementioned points are closely connected to liquefaction technology selection (either single mixed refrigeration or nitrogen Brayton cycle) as well as the rotating equipment used: Firstly, regarding energy use, the refrigeration compressor is the main power consumer in an SSLNG plant (in addition to pumps and smaller compressors). Secondly, a large amount of process leakage is linked to the seals of the rotating equipment. Regarding the third point, operational flexibility, this parameter is closely related to the deployed compressor and expander, and their respective process characteristics. Lastly, the footprint and equipment size have an impact on the installation costs and ultimately CAPEX.

Often, especially in a nitrogen Brayton cycle, compressors as well as warm and cold turboexpanders are supplied as single skid each: that is, a nitrogen compressor skid as well as both warm and cold expander compressors installed on another skid. To reach their future objectives, some SSLNG plant operators are taking new approaches that combine these two technologies: compressor and expander applications are installed on one single gearbox and skid – this is called a Compander. This approach is already used in other industry segments and applications, including LNG carriers. Atlas Copco's first land-based LNG refrigeration Compander was installed back in 2002 at a plant in Norway. The Compander design allows for only one gearbox on which compressor and expander stages are mounted, one oil system, one control system and one seal gas panel – instead of having all of these components twice. By applying these bridging technologies, SSLNG plants are finding new ways to improve OPEX while at the same time reducing the financial burden on new projects. In this case study, we discuss how SSLNG plants in Norway and customers in other places have implemented Atlas Copco Gas and Process integrally geared technology that merges the functions of a centrifugal compressor and turboexpander into one compact Compander unit. In addition, different configurations of separate compressors and expanders are discussed and compared to a single-skid (Compander) solution.

During the discussion, the benefits of a Compander compared to single and separate equipment designs are evaluated.
Innovative ROV Manipulator Powered by Artificial Intelligence to Decrease Risk in Subsea Operations
Authors: Bakr Wael
Published: November 2019

The scope of this paper is to present a new and innovative technology to enhance the performance of subsea installation and construction activities while reducing the risk for both human life and the environment. The conventional method of conducting subsea installation in diver-accessible areas is usually by the use of saturation diving systems and teams. This poses a significant operational risk on the lives of the team, the environment, and the subsea assets in the area, along with also having operational limitations. This paper presents a technology that reduces this risk and enhances subsea installation activities altogether.

The technology presented is an intelligent manipulator that can be installed on Remotely-Operated Vehicles (ROVs). The system relies on artificial intelligence, the geometry of machine making, power, and accuracy to enhance subsea installation operations. Through the use of 3D point cloud technology, the system is able to give accurate views and measurements of the surrounding environment, allowing for accurate path determination and decision making.

The result of the technology is that the ROV manipulator is able to mimic human divers’ mental and physical abilities in different modes of action during subsea installation operations, especially in hazardous environments. This enables such operations to be performed faster and in a more cost-effective manner. Moreover, a key result of the use of this technology is eliminating the huge risk suffered by human divers in hazardous saturation diving environment.

With the use of this technology, the industry would be able to utilize ROVs to conduct diver-less subsea installation activities in a safer, more efficient, and more cost-effective manner than by using saturation diving systems and teams.
Utilizing Machine Learning for a Data Driven Approach to Flow Rate Prediction
Authors: Alkhalaf Ayman , Isichei Obi , Ansari Najmul , Milad Rashad
Published: November 2019

In this study, we aim to demonstrate how machine learning can empower computational models that can predict the flow rate of a given well. Given current real-time data and periodic well tests, this new method computes flow rates using data-driven model. The computational model is based on analyzing the relations and trends in historical data. Relational databases include huge amounts of data that have been accumulated throughout decades. In addition, there is a large number of incoming operational data points every second that gives a lot of insight about the current status, performance, and health of many wells. The project aims to utilize this data to predict the flow rate of a given well.

A variety of well attributes serve as inputs to the computational models that find the current flow rate. Artificial Neural Networks (ANN) were used in order to build these computational models. In addition, a grid search algorithm was used to fine-tune the parameters for the ANN for every single well. Building a single unique model for every well yielded the most accurate results. Wells that are data-rich performed better than wells with insufficient data. To further enhance the accuracy of the models, models are retrained after every incoming patch of real-time data. This retraining calibrates the models to constantly represent the true well performance and predict better. In practice, Flow rate prediction is used by production engineers to analyze the performance of a given well and to accelerate the process of well test verification. One of the main challenges in building unique models for every well is fine-tuning the parameters for the artificial neural networks, which can be a computationally intensive task. Parameter fine-tuning hasn't been discussed in previous literature regarding flow rate prediction. Therefore, our unique approach addresses the individuality of every well and builds models accordingly. This high-level of customization addresses the problem of under-fitting in ANN well models.
First CO2-EOR Project of the Middle East, Lessons Learnt and Future Plan after Two Years of Injection
Authors: Alklih Mohamad Yousef , Al Hammadi Khaled Eissa
Published: November 2019

Experiences gained from CO2 flooding to improve oil recovery worldwide indicates that considerable amount of remaining oil can be recovered with miscible CO2 injection under appropriate conditions. Though its performance in the heterogeneous Middle Eastern carbonate reservoirs has not been well demonstrated yet, it is most likely going to be the future hydrocarbons recovery process in Abu Dhabi after the successful implementation of the first miscible CO2-EOR pilot in 2009 by ADNOC Onshore. In 2016, ADNOC Onshore embarked on field scale implementation of CO2 injection; making it an integral part of the company's overall strategy to utilize CO2 as one alternative option to the expensive HC gas and address related key technical and business aspects.

The currently implemented CO2-EOR has been facing several complexities and challenges including, but not limited to, sustainability of CO2 supply, achieving miscibility conditions, optimization of production and injection, reservoir modeling issues, HSE risks, suitability of monitoring strategy, keeping the CO2 concentration levels within the existing plan design limits, maintaining the integrity of the facilities, associated operating costs and expansion of field development by CO2-EOR.

A number of mitigation plans and actions have been also put in place to ensure the smoothness of operations and therefore maintain the positive impacts of enhanced oil recovery by CO2 injection. Strong management support, multi-disciplinary data integration, continuous surveillance and pro-activeness are considered as the pillars for CO2-EOR success. This work aims to discuss the lessons learned from the ongoing development of CO2-EOR, after 2 years of implementation, and the way forward for the future development phases.
An Automated Kick Alarm System Based on Statistical Analysis of Real-Time Drilling Data
Authors: Mao Youli , Zhang Peng
Published: November 2019

Early influx/kick detection has been one of the most important focus areas for drilling risk management because it enables the crew to take corrective actions that can minimize the danger and cost associated with the event. This work presents an automated influx alarm system that can analyze real-time drilling data using a statistical approach and raise early kick alarms of different levels. Two real-time trend-analysis methods, the divergence of moving average (DMA) and the divergence of moving slope average (DMSA), are applied to quantify trend evolutions of three indicators: normalized rate of penetration (D-exponent), flow rate, and mud pit volume. An overall kick index is then calculated as a weighted summation of the variations in three kick indicators. An alarm is triggered after the calculated kick index surpasses a preset threshold. This automated system is tested against historical drilling data from 15 wells, of which a total of 23 kick events are recorded. The results show that all actual kick events are captured at an average of 8.5 minutes before the recorded time. The ultimate goal of this work is to apply such a highly automated system for early kick detection from real-time drilling data, without requiring additional downhole sensors or expensive flow meters.
Breaking New Grounds and Records for Unconventional Reservoirs Characterization Using the New Formation Testing and Sampling Technology
Authors: Kelkouli Mohammed , Zaggas John , Boudiba Younes , Akham Abderrahmane , Boumahrat Riad , Ferraz Salah , Bellabiod Sofiane
Published: November 2019

An exploration deep well crossing two reservoirs with different quality and properties, having an objective of: Fluid identification and sampling in extremely tight section (∼0.02mD/cP mobility) as well as in another section that is suspected to be depleted with very high overbalance exceeding legacy tools, knowing the hydrostatic pressure being ∼9500psia.

Wireline formation tester was run using single probe, leading to 65% of tight stations, the rest were valid but with very low mobility. This exposes the tool to an increasing pressure differential exceeding its physical limit and leading to damaging it. This makes any further analysis impossible. The toolstring was upgraded with latest technology of WFT, that is a merge between probe based and dual packer modules. This new technology was designed with extreme environments in mind, that allows sampling in all mobility range from extreme tight to very high with its capability of holding up to 8000psia differential pressure.

In the job described here, some of the tested reservoir sections were differentially depleted, something unknown to customer as this was an exploration environment. Since this information were not know even after the completion of the first and second run, a third run was carried out with the objective of re-investigating the same depths performed by the single probe, but this time 3D Radial Probe was used instead. This gave the advantage of taking the pressure down to almost 0 psia. The potential hydrocarbon zone which was bypassed (seen dry with single probe) was then tested with 3D radial probe giving a reservoir pressure of 2864psia with a mobility of ∼300mD/cP where gas condensate was identified and captured. Now for the extreme tight reservoir section, in combination with high hydrostatic, the mechanical limitation of traditional tools remains the same making sampling and/or fluid ID impossible. An attempt was made using the 3D radial probe, and despite the extreme low mobility ∼0.02mD/cP, an identification of the reservoir fluid (water) was successfully completed without any issue.

The use of 3D Radial Probe technology gave a completely different picture from what was expected, enabled the completion of all objectives and made the impossible (with conventional technology) possibly and easily achievable. This resulted in changing the well strategies accordingly and complete the well successfully. The new technology made the testing of unconventional reservoirs a reality.