Specific Depth Research Articles

Germination of Triticum aestivum L.: Effects of Soil–Seed Interaction on the Growth of Seedlings

Seed size, sowing depth, and seed disinfection can affect seed germination and seedling establishment, which, in turn, can directly affect crop growth and yield. The current study was comprised of two experiments, the first of which was conducted in the laboratory, and a second which was performed under glasshouse conditions. The objective of these experiments was to investigate the effects of seed size, sowing depth, and seed disinfection on seed germination and initial seedling growth of selected wheat (Triticum aestivum L.) cultivars. The treatments in laboratory experiment were arranged in a completely randomized design, which included: (Ι) four wheat cultivars (Pishgam, Haydari, Soissons, and Mihan), (ΙΙ) two seed size classes (x < 2.25 mm, and x > 2.25 mm), and two disinfection treatments (no-disinfection and disinfection), (ΙΙΙ) with five replicates. In addition to the aforementioned treatments, the effect of planting depth (4, 6, and 8 cm) was also investigated in the subsequent glasshouse experiment. The best results were obtained at a sowing depth of 4 cm, in the non-disinfected treatment, using large seeds. In contrast, the lowest percentage and speed of seed germination and vigor index were observed in seeds sown at 8 cm depth, in the disinfected seed treatment, using small seeds. Large seeds contain larger nutrient stores which may improve seed germination indices, which would therefore result in improved percentage and speed of seed germination, followed by faster coleoptile and seedling growth, higher seedling dry weight and seed vigor. These data also illustrated that seed disinfection in the Pishgam and Haydari cultivars had inhibitory effects upon coleoptile growth and seedling length, which could be related to the fungicide’s chemical composition. Unlike other cultivars, disinfection did not show a significant effect on the Soissons cultivar. Based on our data, in order to improve both the speed of wheat seed germination and subsequent plant growth and development; it is necessary to select high-quality, large seeds, planted at a specific planting depth, which have been treated with an effective disinfectant; all of which will be specific for the wheat cultivar in question. Overall, the current study has provided useful information on the effect size seed, sowing depth, and disinfection have upon germination characteristics and seedling growth of wheat cultivars, which can form the basis for future field scale trails.

A Bayesian framework to assess and create risk maps of groundwater flooding

Groundwater flooding can cause severe damages to homes, utilities, and infrastructure and yield significant economic and social costs. Numerical models are used to understand these events and are the basis to produce imagery products for risk management and communication. However, such maps are generally produced using forward model simulations, and most of the mapping products are still deterministic. In contrast to pluvial and fluvial floods, an open issue in the analysis of susceptibility to groundwater flooding is the lack of probabilistic assessment and mapping products recognizing parametric uncertainty. Hence, we propose a Bayesian-based framework to create probabilistic risk maps and to identify the susceptibility to groundwater flood events. We aim to assess the spatial distribution and temporal variability of groundwater flooding by decomposing the uncertainty and the sensitivity of distributed groundwater numerical models. The scheme involves the use of the elementary effects method, the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, and the exploration of the predictive posterior distributions of the groundwater heads to evaluate the susceptibility according to exceedance levels. We use the proposed Bayesian framework with a numerical model that simulates the groundwater flood event that occurred in the valley of the Alz River in 2013. This study developed two types of susceptibility maps based on the exceedance probability of certain groundwater levels and specific cellar depths. The Bayesian inference supports the parameter estimation and thereby increases the spatial confidence of the areas susceptible to inundation. This study shows that maps of susceptibility to groundwater flooding can be built over one single event models and acknowledge the inherent spatial and temporal uncertainty of such events.

Depth-dependent dispersion compensation for the micron resolution optical coherence tomography with a time-frequency analysis method

In the noninvasive imaging of the samples such as biological tissues with various forms of OCT, the dispersion effect would seriously influence the image contrast and resolution. Compared with the invariant dispersion, the sample-induced dispersion is much more difficult to be compensated because it is depth-dependent. In this work, we proposed a time-frequency analysis method to compensate for the depth-dependent dispersion without the pre-knowledge of the dispersive property of the tissue. With the Radon-Ambiguity transform and the fractional Fourier transform the dispersion amount corresponding to the specific depth could be calculated and compensated. The validity of this algorithm was first demonstrated by the simulation of the compensation of the water-induced dispersion at the micron resolution. Furthermore, the TiO2 phantoms and the fingertip of a healthy human volunteer were measured with the common-path micron resolution optical coherence tomography system. The experimental results revealed that the image resolution acquired by the method proposed could be improved by a factor of 2–3. This work can be helpful for dispersion compensation in other optical fields.

Layered feature representation for differentiable architecture search

Differentiable architecture search (DARTS) approach has made great progress in reducing the computational costs of designing automatically neural architectures. DARTS tries to discover an optimal architecture module, called as the cell, from a predefined super network containing all possible network architectures. Then a target network is constructed by repeatedly stacking this cell multiple times and connecting each one end to end. However, the repeated design pattern in depth-wise of networks fails to sufficiently extract layered features distributed in images or other media data, leading to poor network performance and generality. To address this problem, we propose an effective approach called Layered Feature Representation for Differentiable Architecture Search (LFR-DARTS). Specifically, we iteratively search for multiple cell architectures from shallow to deep layers of the super network. For each iteration, we optimize the architecture of a cell by gradient descent and prune out weak connections from this cell. Meanwhile, the super network is deepen by increasing the number of this cell to create an adaptive network context to search for a depth-adaptive cell in the next iteration. Thus, our LFR-DARTS can obtain the cell architecture at a specific network depth, which embeds the ability of layered feature representations into each cell to sufficiently extract layered features of data. Extensive experiments show that our algorithm solves the existing problem and achieves a more competitive performance on the datasets of CIFAR10 (2.45% error rate) , fashionMNIST (3.70%) and ImageNet (25.5%) while at low search costs.

Development of deeply focused microwave lens applicator for efficient hyperthermia treatment

In this paper, a deeply focused microwave lens applicator is investigated for hyperthermia treatment. The lens applicator consists of a double spiral antenna (DSA) and frequency selective surface (FSS) as superstrate. The double spiral structure is designed on the top of the upper substrate (Substrate-1), the slotted ground plane is placed between the upper and lower substrate (Substrate-2), and the microstrip feed line is printed on the bottom of the lower substrate. The overall size of the proposed antenna is 32 × 32 × 3.27 mm3. Moreover, an FSS structure (as superstrate) is designed, which has a size of 64 × 64 mm2 (consists of a 4 × 4 unit cell). The FSS structure behaves as a lens that converts the bidirectional field pattern of DSA into the unidirectional pattern, which improves the focusing ability of the proposed applicator towards the phantom. The lens applicator is simulated with heterogeneous phantom (layers of skin, fat, and muscles), and the performance of the applicator is evaluated in terms of specific absorption rate (SAR), penetration depth (PD), and effective field size (EFS). The lens applicator is fabricated and experimentally validated in the presence of an artificial phantom. The measured results are in close agreement with the simulated one. Further, the performance of the applicator is analyzed for a deeply placed irregular-shaped tumor (at 15 mm from the skin surface). The study of temperature distribution is done, and the peak value of temperature is obtained as 43 °C with 2.5 W of microwave power given to the antenna. The temperature value around the tumor is obtained in the range of 41–45 °C, which is suitable for effective hyperthermia treatment.

Optimal layout design of floating offshore wind farms

This paper proposes a method to optimize the layout design of floating offshore wind farms (FOWFs), in order to maximize the energy efficiency over a year. It is assumed that each wind turbine be installed on a semi-submersible platform, and that each floating platform be repositioned depending on wind conditions. The platform repositioning is realized by the aerodynamic force applied on the turbine's rotor, and the force vector on each turbine is adjusted by manipulating the axial induction factor and the nacelle yaw angle of each turbine. The design parameters for FOWF layout optimization are the neutral positions of the platforms, the anchor distance and angle, and the cable length. For a site with specific sea depth and wind rose, the layout design problem is formulated as a constrained optimization problem and is solved using an iterative optimization procedure. It is demonstrated that the developed method increases energy generation of a 6 × 6 FOWF by 2.4% compared to the regular layout, and gives comparable results with a published result that assumes a repositioning mechanism with additional actuators.

Simplified retinal 3D projection rendering method and system.

A simplified rendering method and system for retinal 3D projection using view and depth information is proposed and demonstrated. Instead of vertex calculations, image-based techniques, including sub-image shifting, image fusion, and hole filling, combined with the depth information, are used to render the multi-view images in a display space with specific discrete depth coordinates. A set of time-division multiplexing retinal 3D projection systems with dense viewpoints is built. A near-eye display of a 3D scene with complex occlusion relationships is realized using the rendering method and system. The eye box of the retinal projection system is enlarged, and the accommodation response of the eyes is evoked at the same time, which improves the visual experience. Rendering tests are carried out using simple and complex models, which proves the effectiveness of this method. Comparative experiments prove that the proposed retinal projection method can obtain high-performance 3D images comparable to the super multi-view display method while simplifying the rendering process. Additionally, the depth of field of the experimental system can cover most of the vergence accommodation conflict sensitive range of the human eye.

Effective coefficient of diffusion and permeability of firn at Dome C and Lock In, Antarctica, and of various snow types – estimates over the 100–850 kg m<sup>−3</sup> density range

Abstract. Modeling air transport through the entire firn column of polar ice sheets is needed to interpret climate archives. To this end, different regressions have been proposed in the past to estimate the effective coefficient of diffusion and permeability of firn. These regressions are often valid for specific depth or porosity ranges only. Also, they constitute a source of uncertainty as evaluations have been limited by the lack of reliable data of firn transport properties. To contribute with a new dataset, this study presents the effective coefficient of diffusion and the permeability at Dome C and Lock In, Antarctica, from the near-surface to the close-off (23 to 133 m depth). Also, microstructure is characterized based on density, specific surface area, closed porosity ratio, connectivity index, and structural anisotropy through the correlation lengths. All properties were estimated based on pore-scale computations from 3D tomographic images of firn samples. The normalized diffusion coefficient ranges from 1.9 × 10−1 to 8.3 × 10−5, and permeability ranges from 1.2 × 10−9 to 1.1 × 10−12 m2, for densities between 565 and 888 kg m−3. No or little anisotropy is reported. Next, we investigate the relationship of the transport properties with density over the firn density range (550–850 kg m−3), as well as over the entire density range encountered in the ice sheets (100–850 kg m−3), by extending the datasets with transport properties of alpine and artificial snow from previous studies. Classical analytical models and regressions from literature are evaluated against the estimates from pore-scale simulations. For firn, good agreements are found for permeability and the diffusion coefficient with two existing regressions of the literature based on open porosity despite the rather different site conditions (Greenland). Over the entire 100–850 kg m−3 density range, permeability is accurately reproduced by the Carman–Kozeny and self-consistent (spherical bi-composite) models when expressed in terms of a rescaled porosity, ϕres=(ϕ-ϕoff)/(1-ϕoff), to account for pore closure, where ϕoff is the close-off porosity. For the normalized diffusion coefficient, none of the evaluated formulas were satisfactory, so we propose a new regression based on the rescaled porosity that reads D/Dair=(ϕres)1.61.

Digitalization of visual discrimination threshold and acceptable tolerance of color depth by psychophysical experiments

AbstractColor depth is of great importance to both dyes and dyeing. The assessments of properties such as color fastness, relative dye strengths require dyed fabric to be adjusted to a specific depth level. However, the study of discrimination threshold and acceptable tolerance of color depth is limited. In this study, we attempted to investigate them. Acceptability (Pass/Fail) psychophysical visual experiments were performed twice by 16 normal color version observers on approximately 1206 samples for 6 standard depths in 3 hues, yielding approximately 40,000 visual assessment data points. The color depth formula, Yang3, which performed best in linearity to color depth in a previous study, was selected to calculate the color depth values YCD3 of the samples. The calculated and the visual data were bridged statistically. Experimental results show that the average discrimination threshold and acceptable tolerance of color depth are approximately 0.45 and 2.15 in YCD3, respectively. Furthermore, the details of different hues, lighter and deeper, male and female perspectives were analyzed and discussed. The Yang3 formula exhibited uniformity at different standard depths, as expected.

Neural Network and Logical Fuzzy application in Brazilian Carbonate formations using conventional well logging, NMR and core data for permeability prediction

Petrophysical information, such as permeability and porosity, is of great importance for oil reserve evaluation. Rock petrophysics measurements involve some degree of uncertainty because conventional well logging and nuclear magnetic resonance data are indirect measurements. Data from core samples are more accurate, depending on the laboratory conditions, but this information belongs to a specific depth and does not represent an entire formation, especially when carbonate formations are present. Carbonate formations are characterized by their variation in porosity systems. Such porosity can be defined as intercrystalline, intergrain, moldic, vuggy and fracture and this parameter is linked with permeability values in different ways. In this work we compare the results obtained from the applications of neural network and fuzzy logic using conventional well logging, nuclear magnetic resonance data and information from core samples for permeability prediction. After using these two techniques, which can be considered efficient tools for uncertainty evaluation, a statistical coefficient called R2 shows better results when using logical fuzzy.

Evaluation of Microhardness of Two Bulk-fill Composite Resins Compared to a Conventional Composite Resin on surface and in Different Depths.

Statement of the Problem: One of the problems with light-cured composite resins is the limitation and inadequate depth of curing and polymerization, resulting in low surface microhardness and restoration failure.Purpose: The present study aimed to compare the surface microhardness of two different bulk-fill composite resins and one conventional composite resin using the Vickers microhardness test.Materials and Method: In the present in vitro study, 108 samples from two different bulk-fill composite resins (Tetric N Ceram and Xtrafil) and one conventional composite resin (Filtek Z250) were prepared in metallic molds (2×4×10 mm) (n=36 for each composite resin). Six samples from each composite resin (n=6) underwent a hardness measurement test at specific depths (0.1, 1, 2, 3, 4 and 5mm). The samples were then stored at 37ºC for 24 hours, followed by a microhardness test at the depths mentioned above.Results: In all the composite resin samples, microhardness decreased with an increase in depth. The highest microhardness was recorded in Filtek Z250, followed by Xtrafil, with no significant difference. The lowest microhardness was recorded in Tetric N Ceram bulk-fill. Both bulk-fill composite resins at all the depths exhibited depth-to-surface standard microhardness (>80%).Conclusion: According to the results, both evaluated bulk-fill composite resins exhibited favorable surface microhardness up to a depth of 5 mm.

Assessment of the potential for underground hydrogen storage in salt domes

The study concerns the critical issue of large-scale hydrogen storage in salt domes. The article aims to present the methodology for the hydrogen storage potential assessment for salt domes. The method considers the size of storage caverns, their depth, the influence of convergence, and the geological structure of the selected salt domes. Statistical analysis of data from the underground cavern storage facility in the Mogilno salt dome allows determining the probability of constructing a salt cavern of a specific volume and depth in the selected salt domes. Estimates based on the developed methodology indicate that the average hydrogen storage potential for the analyzed salt domes ranges from 125.7 TWht after the first filling to 83.8 TWht after 30 years of operation. The maximum storage potential ranges from 178 to 155 TWht, respectively. In the case of the largest analyzed salt dome, where one may construct salt caverns at a depth that ensures moderate convergence, the storage potential amounts to 34.3 TWht after first filling. The presented methodology is the next phase of the research, which refines the previous estimates, allowing for more accurate forecasts of rock salt deposit capacity in terms of hydrogen storage. The presented problems are of interest to countries considering large-scale hydrogen storage, geological survey organizations, companies producing electricity from renewables, and petrochemical companies considering underground hydrogen storage in salt caverns.

CALCULATION OF CEMENTING MATERIAL WITH PLUG BALANCE METHOD AT PLUG CEMENT PROGRAM OF WELL X FIELD Y

A cement plug is a method to place a plug to a specific depth using cement to close the well, preventing lost circulation, sidetracking at the beginning of directional drilling, and to provides a place for an open hole test. The cement plug method used in this research is the balanced plug method. This research was conducted by collecting data on Well X, in the form of well profile data covering casing and tubing dimensions. Furthermore, laboratory data for cement and additives are used. Results of the research showed that the total volume of cement slurry needed is equal to 29.455 bbl, the number of sacks of cement for cementing the open end interval of 81.4 meters is as much as 155 sacks of cement, and the total volume of fluid required to push the cement slurry into a cementing zone is equal 64.15 bbl.

Aquifer Characterization Using Fiber Bragg Grating Multi-Level Monitoring System.

Groundwater responses measured from multiple wells at different depths are essential for delineating the aquifer heterogeneity using hydraulic tomography (HT). In general, conducting HT requires many wells because traditional well monitoring is usually partially open at a specific depth interval or is fully penetrating. Accordingly, conducting an HT survey is typically costly and time-consuming. To tackle these issues, a new multi-level monitoring system (MLMS) for the HT survey was developed using the fiber Bragg grating (FBG) technique. This FBG MLMS could collect the depth-discrete groundwater observations from a fully penetrated 2-inch well. Three field campaigns were conducted to validate the capability of the FBG MLMS for HT surveys. The results show that the accuracy and stability of this MLMS are reliable and that FBG MLMS is beneficial for conducting an HT survey. Specifically, compared to the traditional monitoring well in an injection event, this FBG MLMS can concurrently cause an increase in the number of cross-hole tests several times and collect many more head observations than the standard methods, resulting in the observed flow fields efficiently reaching ergodic conditions and effectively improving the accuracy of the estimated hydraulic heterogeneity. Therefore, the FBG MLMS could be an alternative MLMS for efficiently and economically conducting an HT survey.

Evaluation of Soc in a Pine and Broadleaved Mixed Forest Soil of a Nature Reserve in Guangdong Province China

The concern on the role of soil in the global carbon budget and effects of SOC decline on soil quality has been incorporated in international treaties. In Article 3.4 of the Kyoto protocol, soil and forests has been identified as a potential sink of carbon (SOC) that nations tends to establish greenhouse gas inventories and carbon management authorities. Sanchading Nature Reserve Forest Ecosystem and Wildlife study site covers a total area of 2044.2 hectares covering high specie richness of about 1,100 kinds of plants. Soil chemical analysis of the reserve site was conducted at specific depth (0-25cm and 25–50cm). Effect of plant stand types based on broad pine and broadleaved mixed forest (30.24±1.35, 11.71 of 4.49 coefficient variations at 0-25cm depth, while 25–50cm was 26.65±2.49, 21.53 at 9.33). Correlation analysis of NMC, BD, pH, EC and chemical properties showed highest at 51g*kg and 49g*kg at both depths. Duncan’s critical evaluation of SOC(105.62) and heavy metals revealed Zn to be highest (58.20±3.37). Analytical approaches of SOC and associated factors were comparatively reviewed while the study site shows that correlation analysis of the influence of soil properties on SOCc and SOCd (0-50cm) indicated less disturbances and good forest management regime were in place. SOC concentration and effect of pollution and other forest soil environmental disturbances shows negative impact on terrestrial ecosystems. Cumulative evaluation of SOC distribution further supports that pine and broadleaved mixed forest stand exhibits high potential of carbon sequestration.

Probabilistic bearing capacity of spudcan foundations under combined loading in spatially variable soils

Spudcan foundations are widely used in the offshore gas and oil industry to support mobile jack-up drilling rigs. During the service period, the spudcan foundations need to resist large vertical-horizontal-moment (VHM) loads that are transmitted from the superstructure. The bearing capacity of foundations in complicated stress conditions is usually based on VHM failure envelopes. These are commonly constructed by using numerical methods where the soil properties are assumed to be deterministic, ignoring the inherent spatial variability. This paper investigates the influence of spatially variable undrained shear strength and embedment depth on the capacity of spudcan foundations under VHM combined loads. The linearly increasing undrained shear strength with depth obeying log-normal distribution was taken into account. Probabilistic failure envelops were constructed to analyse the effect of spatial variability on the bearing capacity of spudcan foundations at various embedment depths when subjected to different combinations of VHM loads. The influence of horizontal scale of fluctuation for a specific embedment depth was also investigated. The results indicated that under combined loading the embedment depth significantly influenced the shape and size of failure envelopes. The probability of failure at each embedment depth based on the obtained probabilistic failure envelopes was intuitionally represented by means of a factor of safety, which can provide specific guidance for foundation reliable designs.

An inference of the wading depths of the cranes in wintering wetlands through photographic sampling: a case study of black-necked cranes (Grus nigricollis) in Caohai Wetland, China

Several overwintering crane species like Black-necked cranes (Grus nigricollis) mainly depends on wetlands for foraging or roosting, preferring stable water depths. Understating the wading depths of cranes is a pressing concern for the better management of wetlands and robust conservation of the overwintering cranes populations. Yet, practically it is very difficult to precisely measure the wading depths due to several limitations like, inaccessibility and sampling difficulties. In the current study a sample of 1288 wading photographs of cranes, based on the constancy of proportion of tibiotarsus to tarsometatarsus was taken in Caohai wetland situated in the Northwest Guizhou Province of southwest China. Caohai Wetland is the biggest overwintering wetland around the world, and a very promising area to infer the exact ranges of wading depths of these cranes. The ratio of tibiotarsus to tarsometatarsus of the cranes standing on the lands and the ratio of tibiotarsus to the rest of tarsometatarsus of the cranes standing in water were measured; to infer the projection depths of the part of tarsometatarsus submerged in water, which was used to calculate the accurate depth range of the cranes by comparing with the referenced values. According to the results, 89.92% of individuals preferred the water depths from (0–20] cm, 76.11% preferred (0–10] cm% while water depths for 49.04% individuals was (0–5] cm. Thus we conclude that the Black-necked Cranes prefer a depth range of (0–10] cm. This water depth may be relative to the swamps around the lake, which are very important foraging and roosting sites for cranes, For better habitat management, we strongly recommend paying special attention to swamps with specific water depth ranges, particularly when the water level changes.

Depth profiling of epidermal hydration inducing improvement of skin roughness and elasticity: in vivo study by confocal Raman spectroscopy

Skin hydration in the stratum corneum plays an important role in skin condition, and skin efficacy properties are influenced by its hydration level. However, few studies have identified the correlation between changes in skin hydration content and skin characteristics by skin depth level. This study aims to determine how changes in skin hydration at specific depth levels affect skin condition by long-term tracking changes in hydration of stratum corneum and viable epidermis after usage of moisturizer. Ten volunteers were recruited and subjected to in vivo confocal Raman spectroscopy to perform water content profiling at skin depths of up to 52μm. Mechanical properties of skin were measured using Cutometer and Antera 3D. Skin-elasticity and roughness values observed before and after 15days of moisturizing emulsion use were compared to demonstrate the correlation between observed changes in skin efficacy parameters and skin water content at specific depths. Significant increase in relative water content at specific depths was observed in this study. Among mechanical properties of skin, only R4, R6, and R8 parameters demonstrated significant changes. Additionally, rates of change in values of the R6 and R8 parameters revealed a high correlation with water content changes at viable epidermis depths below the stratum corneum. On the other hand, skin roughness parameter showed a correlation with water content changes at the outermost layer of stratum corneum. Results of this study indicate that skin elasticity is influenced by its hydration level at viable epidermis depths and skin roughness at stratum corneum each. This suggests that monitoring depth profiles of water content using in vivo confocal Raman spectroscopy provides a breakthrough in tracking the skin efficacy effect of topically applied substances.

Integration of Distributed Energy Resources to Unbalanced Grids Under Voltage Sags With Grid Code Compliance

The aim of this paper is to analyze the situations in which distributed power generation systems (DPGSs) based on renewable energy sources (RESs) can be controlled when operating under voltage sags. Analytical models for both solar photovoltaic (PV) system and doubly-fed induction generator (DFIG)-based wind turbine (WT) written in the complex form of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Park</i> variables are given. Three kinds of control for the grid-side converter (GSC) of a PV system are compared: constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">forward</i> voltage control (CFVC), balanced <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">positive</i> -sequence control (BPSC) and the proposed BPSC with grid code requirements (BPSC-GCR). Regarding the rotor-side converter (RSC) of a DFIG-based WT, its controllability is studied considering three different-sized DFIG-based WT units: 6 MW (offshore), 2 MW (onshore) and 7.5 kW (setup). The converter limits are also considered. Simulations carried out in MATLAB reveal that a RES-based DPGS can achieve fault ride-through (FRT) when subject to a certain fault (i.e., with a specific duration and depth), but it may be uncontrollable for different-sized units operating under different faults without considering the grid code requirements. Finally, experimental results prove the robustness of the BPSC-GCR method to let GSCs of PV systems achieve FRT under sags.

Development of 1D-Synthetic Geomechanical Well Logs for Applications Related to Reservoir Geomechanics in Buzurgan Oil Field

Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechanical well logs for the production section of the Buzurgan oil field, located in the south of Iraq, using an artificial neural network. An issue with the area of study is that shear wave velocities and pore pressure measurements in some wells are missing or incomplete possibly for cost and time-saving purposes. The unavailability of these data can potentially create inaccuracies in reservoir characterization n and production management. To overcome these challenges, this study presents two developed models for estimating the shear wave velocity and pore pressure using ANN techniques. The input parameters are conventional well logs including compressional wave, bulk density, and gamma-ray. Also, this study presents a construction of 1-D mechanical earth model for the production section of Buzurgan oil field which can be used for optimizing the selected mud weights with less wellbore problems (less nonproductive time. The results showed that artificial neural network is a powerful tool in determining the shear wave velocity and formation pore pressure using conventional well logs. The constructed 1D MEM revealed a high matching between the predicted wellbore instabilities and the actual wellbore failures that were observed by the caliper log. The majority of borehole enlargements can be attributed to the formation shear failures due to an inadequate selection of mud weights while drilling. Hence, this study presents optimum mud weights (1.3 to 1.35 g/cc) that can be used to drill new wells in the Buzurgan oil field with less expected drilling problems.