A Novel Approach to Reservoir Simulation of Hydraulic Fractures: Performance Improvement Using Pseudo Well Connections

Reservoir simulation is used in most modern reservoir studies to predict future production of oil and gas, and to plan the development of the reservoir. The number of hydraulically fractured wells has risen drastically in recent years due to the increase in production in unconventional reservoirs. Gone are the days of using simple analytic techniques to forecast the production of a hydraulic fracture in a vertical well, and the need to be able to model multiple hydraulic fractures in many stages over long horizontals is now a common practice. The type of simulation approach chosen depends on many factors and is study specific. Pseudo well connection approach was preferred in the current case. Due to the nature of the reservoir simulation problem, a decision needs to be made to determine which hydraulic fracture modeling method might be most suitable for any given study. To do this, a selection of methods is chosen based on what is available at hand, and what is commonly used in various reservoir simulation software packages. The pseudo well connection method, which models hydraulic fractures as uniform conductivity rectangular fractures was utilized for a field of interest referred to as Field A in this paper. Such an assumption of the nature of the hydraulic fracture is common in most modern tools. Field A is a low permeability (0.01md-0.1md), tight (8% to 12% porosity) gas-condensate (API ~51deg and CGR~65 stb/mmscf) reservoir at ~3000m depth. Being structurally complex, it has a large number of erosional features and pinch-outs. The pseudo well connection approach was found to be efficient both terms of replicating data of Field A for a 10 year period while drastically reducing simulation runtime for the subsequent 10 year-period too. It helped the subsurface team to test multiple scenarios in a limited time-frame leading to improved project management.

Using ZnCo2O4 Nanoparticles as The Hole Transport Layer to Improve Long-Term Stability of Perovskite Solar Cells

Inorganic metal oxides with the merits of high carrier transport capability, low cost and superior chemical stability have largely served as the hole transport layer (HTL) in perovskite solar cells (PSCs) in recent years. Among them, ternary metal oxides gradually attract attention because of the wide tenability of the two inequivalent cations in the lattice sites that offer interesting physicochemical perperties. In this work, ZnCo2O4 nanoparticles (NPs) were prepared by a chemical precipitation method and served as the HTL in inverted PSCs. The device based on the ZnCo2O4 NPs HTL showed better efficiency of 12.31% and negligible hysteresis compared with the one using PEDOT:PSS film as the HTL. Moreover, the device sustained 85% of its initial efficiency after 240 hours storage under a halogen lamps matrix exposure with an illumination intensity of 1000 W/m2, providing a powerful strategy to design long-term stable PSCs for future production.

Recursive Neural Network-Based Market Demand Forecasting Algorithm for Calligraphy Practice Products

In today’s society, calligraphy, which reflects one’s basic writing skills, is becoming more and more important to people. People are influenced by calligraphy in their studies, work, etc. Improving calligraphy writing skills has become one of the key directions for developing one’s abilities at this stage. As an important means of improving writing skills, calligraphy practice products are attracting more and more attention and purchases. In particular, in recent years, as the market economy has developed in a deeper direction, people’s demand for calligraphy practice products has diversified and calligraphy practice product companies have launched a variety of products to meet the public’s calligraphy practice needs in order to adapt to the reality of consumer demand. However, with the development of the Internet culture industry and influenced by objective factors such as school holidays and seasons, the current market demand for calligraphy practice products is rapidly and dynamically changing, making market changes difficult to grasp and leading to poor sales, which directly affects the profits of calligraphy practice product-related companies. The artificial intelligence neural network method realizes the nonlinear relationship between the input and output of sample data through the self-learning ability of each neuron and has a certain nonlinear mapping ability in prediction, which plays a great role in the market demand prediction of many commercial products. Based on this, this paper proposes a recursive neural network-based algorithm to predict the future demand and development trend of calligraphy practice products through extensive and in-depth research, so as to provide positive and beneficial guidance for enterprises’ future production and sales.

Integrated fracture characterization of Asmari reservoir in Haftkel field

The Asmari reservoir in Haftkel field is one of the most prolific naturally fractured reservoirs in the Zagros folded zone in the southwest of Iran. The primary production was commenced in 1928 and continued until 1976 with a plateau rate of 200,000 bbl/day for several years. There was an initial gas cap on the oil column. Gas injection was commenced in June 1976 and so far, 28% of the initial oil in place have been recovered. As far as we concerned, fracture network is a key factor in sustaining oil production; therefore, it needs to be characterized and results be deployed in designing new wells to sustain future production. Multidisciplinary fracture evaluation from well to reservoir scale is a great privilege to improve model’s accuracy as well as enhancing reliability of future development plan in an efficient manner. Fracture identification and modeling usually establish at well scale and translate to reservoir using analytical or numerical algorithms with the limited tie-points between wells. Evaluating fracture network from production data can significantly improve conventional workflow where limited inter-well information is available. By incorporating those evidences, the fracture modeling workflow can be optimized further where lateral and vertical connectivity is a concern. This paper begins with the fracture characterization whereby all available data are evaluated to determine fracture patterns and extension of fracture network across the field. As results, a consistent correlation is obtained between the temperature gradient and productivity of wells, also convection phenomenon is confirmed. The findings of this section help us in better understanding fracture network, hydrodynamic communication and variation of temperature. Fracture modeling is the next step where characteristics of fractures are determined according to the structural geology and stress directions. Also, the fault’s related fractures and density of fractures are determined. Meanwhile, the results of data evaluation are deployed into the fracture model to control distribution and characteristics of fracture network, thereby a better representation is obtained that can be used for evaluating production data and optimizing development plan.

First Report of the Apple Root-Knot Nematode, Meloidogyne mali, on Maple Trees in Republic of Korea

Meloidogyne mali was originally described in Japan on roots of an apple rootstock (Malus prunifolia) (Itoh et al. 1969) and found on elm trees in Italy, Netherlands, Belgium, France and United Kingdom, and euonymus in the USA (EPPO 2018; Prior et al. 2019). In Italy, the nematode was initially described as a new species, Meloidogyne ulmi, but was later synonymized with M. mali (Ahmad et al., 2013). During the study of Meloidogyne species in Republic of Korea, galled roots were found on Acer palmatum collected in Naejangsan National Park, Republic of Korea located at 35°29'29.1"N, 126°55'42.7"E, altitude 147.8 m. Morphologically, the perineal patterns of the females was very similar to M. mali due to rounded dorsal arch and smooth, finely-spaced, indistinct striae. Lateral field shallow, narrow, and faint. Phasmids large, very distinct. Head region of second–stage juveniles flattened anteriorly to hemispherical, slightly set-off from body, without annulations, low head cap. Stylet slender, sharply pointed cone, cylindrical shaft with rounded knob sloping posteriorly. Tail conoid with irregular, and rounded end. Rectum undilated. Several micrographs were made from 25 J2s and females for mean, standard deviation and range. J2s were measured with a body length: 408.2 ± 25.1 (366-449) µm, maximum body width: 15.9 ± 1.0 (14.1-17.9) µm, stylet length: 14.1 ± 0.5 (13.1-15.3) µm, hyaline tail terminus: 10.0 ± 0.9 (8.3-11.0) µm and tail length: 31.7 ± 3.0 (26.0-36.1) µm. Females (n=25) were characterized by a body length: 656.7 ± 102.7 (516-947) µm, a stylet length: 16.4 ± 2.2 (13.9-19.0) µm, a vulval slit length: 22.2 ± 1.8 (19.8-25.7) µm, and a vulva-anal distance: 20.2 ± 2.4 (17.1-25.4) µm. Morphological measurements and configuration of perineal patterns (Fig. 1S) were comparable to M. mali (Itoh et al. 1969; Ahmed et al. 2013; Gu et al. 2020). To confirm pathogenicity, a modified version of Koch’s postulates was conducted in the greenhouse by inoculating 300 eggs from a single egg mass onto each of three, two-year-old A. palmatum plants, grown in sterilized sandy soil. After about one year, symptoms developed on the maple tree roots, with numerous galls containing females and egg masses by visual inspection. In addition, PCR was performed for the 28S rDNA D2-D3 segment and ITS region using the primers D2A, D3B, TW81 and AB28. The resulting sequences (MW522548, MW522549, MW523004 and MW523005) were at least 99% identical to other 28S rDNA D2-D3 segment and ITS region sequences on Genbank (MT406757 and JX978229). The molecular phylogenetic relationships of this species strongly supports M. mali (Fig. 2S). To the best of our knowledge, this is the first report of M. mali in Republic of Korea. The host range of M. mali includes many species which are of economic importance in fruit trees (e.g. apple, chestnut, fig, mulberry), forestry trees (e.g. elm, maple, oak, Yew), and vegetable crops (e.g. cabbage, carrot, cucumber, eggplant, soybean, watermelon). The potential danger to these economically important plants caused M. mali to be added the EPPO Alert List and also the Quarantine List of the Korean Animal and Plant Quarantine Agency. Additionally, in our survey around the Naejangsan National Park, M. mali was not found on other economically important host crops, such as grapes. Although this nematode was not detected other crops, it requires regular monitoring because it poses a serious threat to the future production of these crops.

Forecast of Economic Tight Oil and Gas Production in Permian Basin

We adopt a physics-guided, data-driven method to predict the most likely future production from the largest tight oil and gas deposits in North America, the Permian Basin. We first divide the existing 53,708 horizontal hydrofractured wells into 36 spatiotemporal well cohorts based on different reservoir qualities and completion date intervals. For each cohort, we fit the Generalized Extreme Value (GEV) statistics to the annual production and calculate the means to construct historical well prototypes. Using the physical scaling method, we extrapolate these well prototypes for several more decades. Our hybrid, physico-statistical prototypes are robust enough to history-match the entire production of the Permian mudstone formations. Next, we calculate the infill potential of each sub-region of the Permian and schedule the likely future drilling programs. To evaluate the profitability of each infill scenario, we conduct a robust economic analysis. We estimate that the Permian tight reservoirs contain 54–62 billion bbl of oil and 246–285 trillion scf of natural gas. With time, Permian is poised to be not only the most important tight oil producer in the U.S., but also the most important tight gas producer, surpassing the giant Marcellus shale play.

KOMPARASI METODE MOVING AVERAGE DAN TREND PROJECTION SEBAGAI ALAT UKUR PERENCANAAN PRODUKSI PADA UD. JAYA ABADI KABUPATEN PROBOLINGGO

The purpose of this research is to find out the comparison of forecasting calculations using the moving average and trend projection methods as a means measuring tool in production planning at UD. Jaya Abadi Probolinggo Regency. The type of research used is quantitative descriptive. Population and sample in this research is UD production data. Jaya Abadi Probolinggo Regerency from 2018 to March 2021. Data analysis using the moving average and trend projection methods which aim to predict future production or the next period. The results showed that the value of MAD (Mean Absolute Deviation) and the MSE (Mean Square Error) moving average values are higher than the MAD and the MSE trend projection, so the company you should use trend projection because when viewed from the results of the comparision of MAD and MSE, this method has a smaller error rate than the moving average method. So it can be concluded that the trend projection method can be used in planning bread production at UD. Jaya Abadi Probolinggo Regency

Analysis of technical development of small-sized loaders with on-board swing system

Due to the spread of small-sized loaders with on-board swing system (SLOS), it has become necessary to determine the level of their technical development. To understand the set task, a review of small-sized loaders, their classifications, performance parameters and implements was made. Modern SLOS manufacturers were analysed; their design features; main operating parameters: engine power, load capacity, speed and vehicle weight. An analysis of recent papers describing SLOS performance was conducted. It should be noted that most of them consider specific workflow processes, design features that do not reflect the full range of such machines. To solve this problem, a statistical analysis of theSLOS nomenclature data was performed depending on the classification features and performance indicators. This article presents the assessment of the impact of SLOS performance parameters and classification features on their level of technical development. Based on statistical data, the regression equations of the dependences were obtained: engine power on load capacity; loader weight on load capacity; dependences of performane parameters were plotted. General trends in the technical development of small-sized loaders were established. The vast majority of manufacturers focus on the production of medium-capacity loaders, as they are in the greatest demand. The analysis of the graphs suggests that in the future production of small-sized loaders with the load capacity of up to 1.5 tons, engine power of 60-70 kW and weight of up to 5 tons will increase. We can also predict growing production of compact SLOS with the load capacity of up to 0.5 tons, engine power of 20-30 kW and weighing up to 2 tons, which are widely used in urban landscaping. With the help of the present paper we can predict development trends, establish weaknesses of modern SLOSs and avoid competition when designing new loaders.

Field Experience of an Innovative Downhole Energy Harvesting System

Downhole power harvesting is an enabling technology for a wide range of future production systems and applications, including self-powered downhole monitoring, downhole robotics, and wireless intelligent completions. This paper presents the field experience of an innovative energy harvesting system that was successfully deployed and tested in the harsh downhole conditions of an oil producer. There is a critical need for robust and reliable downhole power generation and storage technologies to push the boundaries of downhole sensing and control. This paper provides an analysis of available ambient energy sources in the downhole environment, and various energy harvesting techniques that can be employed to provide a reliable solution. Advantages and limitations of conventional technique like turbine are compared to advanced energy harvesting technologies. The power requirements and technical challenges related to different downhole applications have also been addressed. The field experience of the novel flow-based energy harvesting system are presented, including the details of both the lab and field prototype design, deployment and testing.

Evaluating the potential of aquaculture in the Hoa Binh reservoir with carrying capacity and water quality indices

Not only does the Hoa Binh reservoir play essential roles in water storage for electricity generation and flood regulation, but also it has great potential to aid aquaculture production. Presently, aquaculture production sits at around 9,200 tons/year; however, a recent MARD circular (#16 in 2015) estimated that maximum production would approach 10,000 tons/year in the productive photic zone. This paper supports increased capacity towards a sustainable commodity production model by optimizing production levels and farming practices. To reach this goal, it is necessary to determine water quality parameters using the Relative Water Quality Index (ReWQI) and carrying capacity (CC) analysis. Data was obtained from 30 sites at upstream, midstream, and downstream sections of the reservoir during the 2019 dry and wet seasons. The results from the ReWQI reflected good water quality potential (rated between 92-100) for aquaculture. The total nitrogen (TN) and total phosphorus (TP) levels of 10,794.9 kg/day and 1,965.4 kg/day, respectively, indicate high biological productivity resulting in strong fish growth potential. CC analysis and overall water quality reflect the potential for sustainable and increased productivity to 22,730.4 tons/year, which is an increase in production of over 13,200 tons/year compared to the current period. To reach a higher yield of 40 kg/year/m3 within each cage (5,040 kg/cage/year), the corresponding increase in number needs to be 4,510 cages based on a common cage size of 126 m3 (6x6x3.5 m). In order to reach these future production goals, this work concludes that the local government should begin spatial planning decisions based on appropriate cage allocation and distribution with respect for regular monitoring of water quality and nutrient load capacity of the environment to reach sustainable aquaculture development.