Academic literature on the topic 'Mate Selection Index (MSI)'

AbstractLook ahead mate selection (LAMS) schemes have been proposed to improve longer-term genetic merit when both selection and crossbreeding are important. We investigate the performance of a LAMS scheme which includes both predicted progeny merit and predicted grandprogeny merit in a mate selection index (MSI). Simulation of a multi-breed beef population, with additive breeding values, direct and maternal breed effects and direct and maternal heterosis was used to compare response from the LAMS scheme to mate selection on progeny merit only (PROG), selection on estimated breeding value (EBV) followed by random mating (RAND) and a structured crossbreeding scheme (CROSS). An additional strategy, LAMS + CO, was similar to LAMS but included a negative weighting on the coancestry of selected animals in the MSI to reduce inbreeding. LAMS gave up to 3% greater response in generation eight than PROG, 4·5% greater response than RAND, and 15% greater response than CROSS. Results from LAMS + CO were very similar to LAMS but inbreeding was 11% less from LAMS + CO at generation eight. The advantage of LAMS and LAMS + CO over PROG in later generations was hypothesized to be the result of positive assortative mating and greater use of maternal effects. Evidence to support the hypothesis of assortative mating was a positive significant correlation of EBVs of mates (sires and dams) in LAMS and LAMS + CO but not in PROG. Strategies PROG, LAMS and LAMS + CO all created closed populations of animals with optimum composite breed proportions.

Purpose Manufacturers and engineers need a practical and operational way to understand sustainable manufacturing and to apply it to their shop floors. The single index enables manufacturing industries to make decisions considering the continuous improvement to increase sustainability performance. The purpose of this paper is to develop a manufacturing sustainability index (MSI) based on lean and sustainability concepts using sustainable-value stream mapping. Design/methodology/approach The methodology of this research is linked to Delphi- analytical hierarchy process (AHP) qualitative assessment with sustainable-value stream mapping quantitative analysis for determining MSI. The Delphi method is used with relevant indicator selection, sustainable-value stream mapping is used to score the relevant indicator with efficiency approach and the AHP method is used to determine the indicator weight. To evaluate the applicability of this framework for assessing sustainability in the manufacturing process, a case study in Indonesian Wooden Furniture was developed. Findings The findings of this research is the framework for evaluating and assessing the sustainability performance of the manufacturing process. Although evaluation of the framework is limited to the furniture industry, there is a methodology potential to reproduce for the other sectors. Research limitations/implications Theoretically, this study has provided a single index to measure performance of the manufacturing sustainability comprehensively at factory level. However, the implementation of the developed model is too limited. More application in different sectors and different industrial sizes is needed. Originality/value The value of this research lies in the novelty of the single index in measuring manufacturing sustainability and the relevant indicators for the furniture industry in Indonesia. The selection of the indicators has involved practitioners in the furniture industry and encompassed economic, environmental and social dimensions. The visualization of indicators through sustainable-value stream mapping is proven to be more practical and helpful for industrialists.

The effect of high temperature treatment on the expression of cytoplasmic male sterility (CMS) was studied using inbred lines of four summer rape (Brassica napus L.) cultivars. The nuclear genotypes of inbred lines from each of the cultivars Karat, Lergo, Marnoo and Regent were evaluated for their ability to maintain pollen sterility in the pol cytoplasm. Seven days' exposure to day/night temperatures of 30/24 °C in a controlled environment led to increased pollen production in all of the F1 populations (F1's) in the study. Maximum reversion to male fertility occurred 6–13 d after removal from the high temperature treatment. There was a significant linear relationship between daily mean temperatures in the field and mean male sterility index (MSI). In Lergo, Marnoo and Regent F1's, the effect of high temperatures on male sterility expression in terms of days to maximum pollen production in the field was accurately predicted by the values obtained in the controlled environment study. For the Karat F1's, the maximum response in the field occurred later than in the controlled environment. Variation in the stability of male sterility was evident in the F1's, indicating the presence of different maintainer genes among the inbred lines of each cultivar. The absence of environment-by-line interactions in the F1's of three cultivars indicated a high degree of stability for this trait. Selection for maintenance of high levels of male sterility may therefore be possible. Key words: Brassica napus, male fertility reversion

An index of a family's success is the caliber of talent it manages to attract and retain through marriage. This fundamental fact in sociology, anthropology, and history has received little attention in the family business field. Parents in Western societies have two windows of opportunity to enhance long-term family success through marriage: first, before their children reach puberty, and later, after they choose spouses for themselves.

AbstractBreeding for drought tolerance using novel genetic resources possessing relevant agronomic and adaptive traits is a key to enhance productivity and food security in wheat growing areas. Herein, the main objectives were (i) to use a combination scoring index (multiple scoring index, (MSI)) for selection of durum wheat genotypes under different drought stress intensities (SIs) (ii) to examine repeatability of the scoring index through bootstrap re-sample method, and (iii) to study the relationship of MSI with some drought-adaptive traits. Sixteen durum wheat genotypes were grown under rainfed and irrigated conditions during three cropping seasons (2012–2015), resulting in different drought SIs, that is, mild (SI < 0.3), moderate (0.3 < SI < 0.6), and severe (SI > 0.6). The average grain yields among test environments varied between 708 and 3631 kg ha−1. The validation of the methodology of scoring index was confirmed by the correlation coefficients between score indices and their original values across different drought SIs. According to MSI, the genotypes G16, G1, and G3 had the best combination of high productivity and high resilience to mild, moderate, and severe drought stress conditions, respectively. These results indicated that the ranking of genotypes varied among different drought SIs, which support the high potential of durum wheat for adaptation to different drought stress conditions. Based on the bootstrap samples, non-repeatable correlations were observed between the estimates of MSI from different levels of stress. The significant correlation between MSI with grain yield and 1000-kernel weight (TKW) under severe drought condition provides evidence that MSI ultimately be considered as a tool for effective selection of drought-tolerant genotypes. The MSI selected genotypes based on high productivity and resilience, to each level of drought SI, and favorable adaptive traits useful for breeding.

In order to reconstruct a high spatial and high spectral resolution image (H2SI), one of the most common methods is to fuse a hyperspectral image (HSI) with a corresponding multispectral image (MSI). To effectively obtain both the spectral correlation of bands in HSI and the spatial correlation of pixels in MSI, this paper proposes an adversarial selection fusion (ASF) method for the HSI–MSI fusion problem. Firstly, the unmixing based fusion (UF) method is adopted to dig out the spatial correlation in MSI. Then, to acquire the spectral correlation in HSI, a band reconstruction-based fusion (BRF) method is proposed, regarding H2SI as the product of the optimized band image dictionary and reconstruction coefficients. Finally, spectral spatial quality (SSQ) index is designed to guide the adversarial selection process of UF and BRF. Experimental results on four real-world images demonstrate that the proposed strategy achieves smaller errors and better reconstruction results than other comparison methods.

By analyzing Maintenance Significant Item (MSI) standard procedures of Maintenance Steering Group-3(MSG-3), building optimal evaluation index of maintenance mode selection, an improved hierarchy model based on MSG-3 is established for evaluation of maintenance mode. Scale selection and layer weight confirmation is improved to solve the sort of index weight in evaluation. It makes maintenance mode selection more reasonable. The hierarchy model is implemented on .NET platform. The simulation result proves the validity of the method.

Water deficiency is a major constraint in wheat production and the most important contributor to yield reduction in the semiarid regions of the world. species related to wheat are valuable genetic sources for different traits including resistance/tolerance to biotic and abiotic stresses. To locate the genes controlling the physiological and agronomic criteria of drought tolerance, disomic addition lines of secale cereale cv. Imperial (donor) into the genetic background of Triticum aestivum cv. Chinese Spring (recipient) were tested under field, greenhouse and laboratory conditions. Disomic addition lines exhibited significant differences for relative water content (RWC), relative water loss (RWL), water use efficiency (WUE) and stomatal resistance (SR), indicating the presence of genetic variation and the possibility of selection for improving drought tolerance. Three physiological variables, RWL, WUE and SR, with high correlation with the stress tolerance index (STI) and germination stress index (GSI), contributed 69.7% to the variability of yield under stress (Ys) in the regression equation. Based on the physiological multiple selection index (MSI) most of the QTLs controlling physiological indices of drought tolerance were located on chromosomes 3R, 5R and 7R. The contribution of addition line 7R to the MSI was 47%. The evaluation of disomic addition lines for STI and GSI revealed that most of the QTLs involved in these quantitative criteria of drought tolerance are located on 3R and 7R. Cluster analysis and three dimensional plots of Ys, yield potential (Yp) and MSI indicated that 3R and 7R are the most important chromosomes carrying useful genes for improving drought tolerance.

Background: To study myocardial performance index in prediabetes in medical staff. To correlate MPI with cardiovascular risk factors. Methods: After subject selection, informed consent was taken from the cases and controls. Detailed history was taken and physical examination was done which included weight, height, body mass index (BMI), waist circumference, hip circumference, waist-hip ratio (WHR) and blood pressure measurement. After physical examination, biochemistry measurements including fasting blood sugar (FBS), post-meal blood sugar (PMBS), serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) were done. Myocardial performance index (MPI) was calculated by 2D-ECHO. Results: BMI, male WHR, serum cholesterol, TG, LDL and MPI was significantly higher in cases (prediabetics) as compared to controls while serum HDL was lower in cases as compared to controls, which was non-significant. Out of 50 prediabetics, 32 (64%) had abnormal MPI with p=0.0001. There was no correlation of MPI with cardiovascular risk factors like BMI, WHR and fasting lipid profile. Conclusion: BMI, male WHR, serum cholesterol, TG, LDL and MPI was significantly higher in cases as compared to controls. However, there was no significant correlation between MPI and other cardiovascular risk factors.

AbstractAlternative index procedures for selection on non-linear profit are quadratic indices, desired gains indices, group or mate selection indices, or direct optimization of responses over multiple generations. In this study a multiple generation time horizon was considered and several linear, quadratic and desired gains indices were compared. Genetic and economic responses over multiple generations were calculated considering a quadratic profit function combining protein yield and days open.Directly optimizing reponse over multiple generations was found to yield slightly higher economic responses (+ < l.5%) than stepwise (each generation) adjustment of a linear index. A constant linear index using base population averages and a quadratic index were found to be less efficient. The quadratic index was less efficient than the linear index when considering multiple generations. Desired gains indices allowed stabilization of base population average for days open, however, forcing considerable economic losses. Relative efficiencies of methods depended on the degree of non-linearity of the profit function.

Mate selection is an attractive breeding strategy for multi-breed beef cattle populations, as it allows selection and crossbreeding to be exploited simultaneously. Two components are required for mate selection; an objective function called a mate selection index (MSI) which describes economic gain as a function of selection and mate allocations (or 'mate selections'), and a mate selection algorithm which finds the mating set which maximises the MSI.

One concern with mate selection is that as breeding decisions are based on progeny merit only (the next generation), short term genetic merit may be maximised at the cost of longer term genetic merit. To address this concern, LAMS (Look Ahead Mate Selection) schemes have been proposed. In LAMS schemes, some weight is given in the MSI to the merit of predicted grand-progeny in mate selection decisions.

To date, there have been few studies predicting the benefits of mate selection in multi-breed beef cattle populations. The impact of mate selection, especially LAMS schemes, on population structure and longer term genetic gain is unknown. Further, the advantages of mate selection when the genetic model of multi-breed populations is extended beyond selection and heterosis to include within breed dominance variance is unknown.

This thesis was designed to investigate three issues:

1. What population structures will emerge when mate selection (including LAMS schemes) is applied in multi-breed populations?
2. What is the effect of longer term implementation of LAMS schemes on genetic merit of multi-breed populations
3. Does mate selection significantly improve the genetic value of a multi-breed population when individual dominance is included in the MSI (relative to other breeding strategies, such as selection followed by mate allocation)?

To investigate the first issue, a deterministic evaluation of mate selection was considered. Mate selection was at the level of genetic groups, where genetic groups were defined by breed composition and selection history. The initial population structure consisted of breeds A and B. Genetic merit of genetic group l was y_l =  µ_l + g^A_lm_A + g^B_lm_B + g^A_jd_ABg^B_k + g^B_jd_ABg^A_k, where g^A_l, the proportion of breed A in progeny genotype l, is calculated as g^A_l = 1/2(g^A_j + g^A_k), where g^A_j and g^A_k are proportions of breed A in parental genotypes j and k respectively. The proportion of breed B in progeny genotype l is calculated similarly. Parameter d_AB, is the F₁ heterosis when breeds A and B are crossed, and µ_l is the mean additive breeding value for progeny genotype l.

The aim of each breeding schemes was to create a new herd in the first generation by importing sires and dams of breeds A and B, and then breed a further generation of progeny in the home herd. The second generation of progeny could be created either by importing more sires and dams, or using sires and dams bred in the home herd in the previous generation. It was assumed no selection was occurring within the foreign populations. Breeding schemes were compared by using the sum of progeny merit over the two generations, for a range of heritabilities and heterosis values. Schemes evaluated were structured crossbreeding (F₁ and F₂ designs), progeny merit each generation as mate selection criteria (PROG_DET), or cumulative merit over two generations as mate selection criteria (CUMUL_DET). CUMUL_DET was a LAMS scheme, as merit of the generation beyond the progeny generation was considered in the mate selection decisions. At all parameter values, PROG_DET and CUMUL_DET gave better cumulative merit than structured crossbreeding designs. This was a result of selecting sires and dams from the whole population rather than within genotypes or genetic groups. The advantage of mate selection strategies over structured strategies was greatest when h²=0.6; up to 1.9% for cumulative merit from CUMUL_DET over the best F₁ cross.

CUMUL_DET gave slightly greater cumulative merit than PROG_DET in all scenarios, with the advantage increasing with greater heritability or greater selection intensities. The advantage of CUMUL_DET over PROG_DET was from allocation of a proportion of purebred matings in the first generation in the home herd in CUMUL_DET. In the second generation, purebred progeny from these selected purebred parents could be crossed to breed F₁ grandprogeny with maximum heterosis and cumulative additive merit from selection. The proportion of purebred matings in the home herd in the first generation increased with heritability (1% of all matings in the first generation when h²=0.1 and 11% when h²=0.6).

To investigate the second issue, response from implementation of tactical (at the individual animal level) LAMS schemes was investigated. The genetic model used included additive breed and maternal effects, and direct and maternal heterosis. For this model, progeny merit of an individual progeny from a mating was PM_i = 1/2(p^T_s + p^T_d)a + p^T_sDp_d + p^T_da_m + p^T_mgsD_mp_mgd where vector p represents the proportion of genes of each breed in sire (s) or dam (d), maternal grand sire (mgs) or maternal granddam (mgd), a is a vector of fixed breed effects (breed means for each breed), a_m is a vector of fixed maternal breed effects, D is a breed x breed matrix of direct heterosis effects, and Dm is a breed x breed matrix of maternal heterosis effects.

Schemes investigated included mate selection with progeny merit only in the MSI (PROG strategy) and mate selection with progeny merit and grandprogeny merit equally weighted in the MSI (LAMS strategy). An additional scheme, COMP, was evaluated which used the contribution of the mating set to progeny with an optimal composite genotype as the MSI. Schemes were assessed using simulation of a single trait (yearling weight) over six generations of a four breed population. It was assumed no selection was occurring in foreign populations. With LAMS, a proportion of matings each generation in all simulations were allocated to breed F1 dams, improving the merit of the next generation, as a three breed cross could be created. LAMS gave the highest cumulative progeny merit over six generations; 20kg greater than PROG, and almost 70kg greater than COMP.

COMP created a population of optimum composite animals after six generations of breeding, with no variation in breed composition among individuals in the population (all animals had the optimum composite genotype). This strategy would be useful for commercial beef producers aiming to produce uniform lines of turnoff progeny.

The performance of LAMS was also evaluated when the genetic model was extended to include individual additive breeding values...

Abstract In the design of cruise ships, it is necessary to make them have an excellent level of energy efficiency and at the same time provide tourists with a good comfort experience. Therefore, it is urgent to explore the balance between cruise comfort and energy efficiency. Based on Maslow’s hierarchy of needs theory, a cruise comfort evaluation system was established combined with the “Cruise Leisure Design Index” issued by China Classification Society; according to the characteristics of cruise ships, a specific “Energy Efficiency Design Index” (EEDI) for cruise ships was proposed. From the perspective of a life cycle, the “Life Cycle Assessment” (LCA) was applied to the cruise design. Meanwhile, the EEDI-LCA cruise ship energy efficiency model was established, and the baseline fitting and comparative analysis were carried out. The combination weighting method combines comfort index and energy efficiency index to establish a cruise ship comfort and energy efficiency evaluation system. The model was verified with a 60,000-ton MSC Sinfonia cruise ship. The results show that the model can find a comparatively good balance between comfort and energy efficiency so that the cruise ship’s energy can be reduced without sacrificing comfort. The balance is a good guide on the selection of cruise design parameters.

Abstract As global energy market conditions demand more reliable energy sources, fields with lower productivity reservoirs struggle to provide cost-effective production options. Multilateral technology (MLT) has been used to improve per-well deliverability and economics, i.e., by increasing the drainage area with less surface footprint. The objective of this work is to review the state-of-the-art of selected completions to provide insights for adoption of MLT technologies including lessons learnt, experiences and some recommendations. Six globally selected demonstrative applications were reviewed to validate the technical assumptions for selecting a particular MLT concept. The first step was to review earlier applications in similar formations to identify the degree of success of these wells and to research possible better candidate reservoirs. Secondly, a screening tool analyzes specific reservoir production conditions where the application of MLT would be compelling. The research was focused on reservoirs with noticeable high-economic potential interest in the application of such technologies. We propose a workflow combining both technical and economic criteria to guide the selection of MLT vs single lateral wells, providing a cost-effective and lower risk decision support tool. We introduced a process to identify the MLT applicability window based on the Activation Index (AI) and the mother to Lateral cost ratio. Our proposed method is likely to be beneficial for operators which struggle to make smart decisions on MLT well concept selection. We show that MLT completions can reduce between 10 and 30% the D&C cost requirements while enhancing field development NPV in the range of 1-21%, and with the potential of promoting fields that were otherwise uneconomic. We discuss here the success factors to make this possible. In addition, one key advantage of MLT is the acceleration of production since multiple zones are available for production much earlier compared to the single zone wells. Furthermore, the implementation of MLT completions is enabling the recovery of reserves on fields where the surface space is constrained due to either a high number of wells or a geographic limitation or even a combination of both.

Abstract The Middle Marrat reservoir of Jurassic age is a tight carbonate reservoir with vertical and horizontal heterogeneous properties. The variation in lithology, vertical and horizontal facies distribution lead to complicated reservoir characterization which lead to unexpected production behavior between wells in the same reservoir. Marrat reservoir characterization by conventional logging tools is a challenging task because of its low clay content and high-resistivity responses. The low clay content in Marrat reservoirs gives low gamma ray counts, which makes reservoir layer identification difficult. Additionally, high resistivity responses in the pay zones, coupled with the tight layering make production sweet spot identification challenging. To overcome these challenges, integration of data from advanced logging tools like Sidewall Magnetic Resonance (SMR), Geochemical Spectroscopy Tool (GST) and Electrical Borehole Image (EBI) supplied a definitive reservoir characterization and fluid typing of this Tight Jurassic Carbonate (Marrat formation). The Sidewall Magnetic resonance (SMR) tool multi wait time enabled T2 polarization to differentiate between moveable water and hydrocarbons. After acquisition, the standard deliverables were porosity, the effective porosity ratio, and the permeability index to evaluate the rock qualities. Porosity was divided into clay-bound water (CBW), bulk-volume irreducible (BVI) and bulk-volume moveable (BVM). Rock quality was interpreted and classified based on effective porosity and permeability index ratios. The ratio where a steeper gradient was interpreted as high flow zones, a gentle gradient as low flow zones, and a flat gradient was considered as tight baffle zones. SMR logging proved to be essential for the proper reservoir characterization and to support critical decisions on well completion design. Fundamental rock quality and permeability profile were supplied by SMR. Oil saturation was identified by applying 2D-NMR methods, T1/T2 vs. T2 and Diffusion vs. T2 maps in a challenging oil-based mud environment. The Electrical Borehole imaging (EBI) was used to identify fracture types and establish fracture density. Additionally, the impact of fractures to enhance porosity and permeability was possible. The Geochemical Spectroscopy Tool (GST) for the precise determination of formation chemistry, mineralogy, and lithology, as well as the identification of total organic carbon (TOC). The integration of the EBI, GST and SMR datasets provided sweet spots identification and perforation interval selection candidates, which the producer used to bring wells onto production.

Abstract This paper discusses integrating common methods and applications for "Rock Typing" (also known as Petrophysical Rock Typing-PRT) including empirical, deterministic, statistical, probalistic and automatic/predictive approaches. Many industry asset teams apply one or more of these methods when creating static reservoir models, using dynamic reservoir simulations, completing petrophysical studies for saturation height models and determining reservoir volumetrics as part of reservoir characterization studies. Our intention is to provide guidance and important information on how and when to use the various methods, so people can make an informed selection. This discussion is important as many disciplines apply these PRT techniques without understanding the pros, cons and limitations of the different methods. An important tool is comparing PRT results from multiple methods. The topics and workflows that are covered focus on various PRT techniques and workflows. We will use case-studies to illustrate the key features and make important comparisons. Key results include comparing pros and cons, how to use and combine multiple PRT techniques and verify results. This paper includes these techniques and workflows;MICP, core analysis and pore throat calibration.Core-Log Integration focused on PRT analysis.Winland, Pittman, Aguilera and Hartmann et.al Gameboard methods.K-Phi ratio, Flow Zone Indicators and Rock Quality Index methods.Classic, Modified and Stratigraphic Lorenz methods.IPSOM and HRA Probabilistic methods.Case Study – Super Plot and Advanced Automatic PRT Method.Special Topics – Carbonate Methods, NMR and Single Well Vertical Line. Practical approaches based on case studies show how PRT analysis can be applied in mature fields to identify by-passed hydrocarbon zones and zones that have a high probability of producing water using open hole, cased hole and production logs. Traditional Rock Typing (PRT) analysis can be applied as a single well technique or as a multi-well method so operations teams can identify additional business opportunities (remedial workovers, infill drilling locations or exploitation targets) and compare reservoir performance with intrinsic rock properties. New applications and additional topics cover single, multiple well approaches and new emerging PRT techniques (including NMR well logs and machine learning). We recommend how to merge classic facies with PRT analysis for 3-D applications including populating a 3D volume.

Abstract The aim of this work is to develop an analytical technique for characterizing formation damage. The oil reservoir of the East Siberian Yaraktinskoe field suffers from salt and organic scales precipitation leading to skin damage. Besides, injection water has sulfates, which precipitate as gypsum in the near wellbore area of production wells and at bottomhole. Historically pressure build-ups (PBU) were used to characterize the evolution and extent of the damage. The use of PBUs leads to the shut in of production. Additionally PBUs in the reservoir provide conclusive results in no more than 22% cases. Based on inconsistent results from PBUs and their cost in production losses, it was of interest to find a better and preferable technique for formation damage control using existing data. The result of that initiative is analytical technique that provides dimensionless productivity index (Jd) range monitoring over time, Jd range comparison to the technical potential and identification of the performance gap range. By identifying the performance gap range, stimulation actions are ordered reestablishing oil production, productivity index (PI) and Jd. The technique is based on transmissibility (kh/µB or T) model derived from Kamal and Pan study (2010) and reservoir pressure (Pres or P) model. Stochastic part of the technique is provided by T and Pres error functions. The functions are probability distribution functions (PDF) derived from comparison of the modeled T and Pres with well test measured historical values. Using this T and Pres models and historical data of liquid rates and bottomhole pressures (BHP), we can calculate current and historical Jd, Jd drop relative to historical performance or potential and oil rate potential increment with uncertainty margins (10th, 50th and 90th percentile or P10-50-90). The margins are calculated from 10000 stochastic iterations of T and Pres within the PDFs of their error. The technique has enabled to find 14 stimulation candidates during 6 month of use. Overall, 15 stimulations were implemented since one well was stimulated twice. Ten of 14 stimulations increased oil production rate by 4161 bbl/day. Five stimulations were economically unsuccessful due to inappropriate stimulation technology implementation. The technique shows acceptable uncertainty level to make efficient and appropriate decisions for the appropriately chosen stimulation technology. Modeled P50 PIs have good match with more than 85% correlation with well test measured PIs after economically successful stimulation. New analytical technique is presented here, which can be utilized as an automatic process without repeating well tests for routine generation of accurate stimulation plan with numerical assessment of success probability and anticipated oil rate increment uncertainty range. Realization of stimulation potential is simplified to the task of appropriate treatment technology selection and implementation for the candidates from the rating.

Abstract Hole cleaning efficiency is one of the major factors that affects well drilling performance. Rate of penetration (ROP) is highly dependent on hole cleaning efficiency. Hole cleaning performance can be monitored in real-time in order to make sure drilled cuttings generated are efficiently transported to surface. The objective of this paper to present a real time automated model to obtain hole cleaning efficiency and thus effectively adjust parameters as required to improve drilling performance. The process adopts a modified real time carrying capacity indicator. There are many hole cleaning models, methodologies, chemicals and correlations, but majority of these models do not simulate drilling operations sequences and are not dependent on practicality of drilling operations. The developed real time hole cleaning indicator can ensure continuous monitoring and evaluation of hole cleaning performance during drilling operations. The methodology of real time model development is by selecting offset mechanical drilling parameters and drilling fluid parameters where collected, analyzed, tested and validated to model strong hole cleaning efficiency indicator that can extremely participate and facilitate a position in drilling automations and fourth industry revolution. The automated hole cleaning model is utilizing real time sensors of drilling and validate the strongest relationships among the variables. The study, analysis, test and validation of the relationships will reveal the significant parameters that will contribute massively for model development procedures. The model can be run as well by using the real time sensors readings and their inputs to be fed into the developed automated model. The developed model of real time carrying capacity indicator profile will be shown as function of depth, drilling fluid density, flow rate of mud pump or mud pump output, and other important factors will be illustrated by details. The model has been developed and validated in the field of drilling operations to empower the drilling teams for better and understandable monitoring and evaluation of hole cleaning efficiency while performing drilling operations. The real time model can provide a vision for better control of mud additives and that will contribute to mud cost effectiveness. The automated model of hole cleaning efficiency optimized the rate of penetration (ROP) by 50% in well drilling performance as a noticeable and valuable improvement. This optimum improvement saved cost and time of rig and drilling of wells and contributed to accelerate wells’ delivery. The innovative real time model was developed to optimize drilling and operations efficiency by using the surface rig sensors and interpret the downhole measurements and that can lead innovatively to other important hole cleaning indicators and other tactics for better development of downhole measurements models that can participate for optimized drilling efficiency.

Following the 2000 European Landscape Convention, a new act strengthening landscape protection instruments has been in force since 2015. It sets forth legal aspects of landscape shaping (Dziennik Ustaw 2015, poz. 774) and introduces landscape audits at the province level. A landscape audit consists in identification and characterization of selected landscapes, assessment of their value, selection of so-called priority landscapes and identification of threats for preservation of their value. An audit complies with GIS standards. Analyses use source materials, i.e. digital maps of physical-geographical mesoregions, current topographic maps of digital resources of cartographic databases, latest orthophotomaps and DTMs, maps of potential vegetation, geobotanic regionalization, historic-cultural regionalization and natural landscape types, documentation of historical and cultural values and related complementary resources. A special new methodology (Solon et al. 2014), developed for auditing, was tested in 2015 in an urban area (Myga-Piatek et al. 2015). Landscapes are characterized by determining their analytic (natural and cultural) and synthetic features, with particular focus on the stage of delimitation and identification of landscape units in urban areas. Czestochowa was selected as a case study due to its large natural (karst landscapes of the Czestochowa Upland, numerous forests, nature reserves) and cultural (Saint Mary’s Sanctuary, unique urban architecture) potential. Czestochowa is also a city of former iron ore and mineral resources exploitation, still active industry, dynamic urban sprawl within former farming areas, and dynamically growing tourism. Landscape delimitation and identification distinguished 75 landscape units basing on uniform landscape background (uniform cover and use of the land). Landscape assessment used a new assessment method for anthropogenic transformation of landscape – the indicator describing the correlation between the mean shape index (MSI) and the Shannon diversity index (SHDI) (Pukowiec-Kurda, Sobala 2016). Particular threats and planning suggestions, useful in development of urban areas, were presented for selected priority landscapes.

Abstract A full suite of integrated online emulsion management system (IOEMS) transforming the handling of decades old crude oil emulsion production issue at field from reactively onsite to proactively online. This technology is made possible with insights on emulsion formation from physics-based molecular models, access of huge database on crude oil properties, emulsion toughness and demulsifier chemistries, coupling with statistical and supervised machine learning application. Intriguingly, this innovation journey began with designing an enhanced oil recovery (EOR) technology in mind. Study on generating stable emulsion for oil recovery was the aim of our pioneering research initially. We successfully developed physics-based models to assess emulsion stability at molecular level. We then applied these models retrospectively for produced emulsion management, with advancement in data science and computational power. The technology concept is to design and plan demulsification strategy based on predicted emulsion stability. The robustness of IOEMS lies in the combination of the goods of accurate interpolated data based on machine learning, with that of extrapolated data from physics-based model. Firstly, mathematical models of relationships between crude properties and emulsion stability index (ESI) were established using statistical method. This led to a good 90% match with laboratory ESI data. Secondly, a demulsifier selection functionality was developed based on machine learning, covering dozens type of demulsifier. We used operating conditions, fluid and demulsifier properties as training data input, with the corresponding lab bottle tests outcomes as training data output to build a classification model via supervised learning algorithms. Its predictive accuracy is at 87%. By bringing the produced emulsion assessment from on-site to online, offshore emulsion sampling and the associated lab bottle tests are minimized. Health safety and environment (HSE) risks are reduced accordingly with the decrease of human intervention in field sampling. The emulsion stability predictive functionality enables operation to prepare early in anticipation of sudden spike of emulsion production and thus, avoiding unplanned well shut in. Furthermore, this function is especially useful when emulsion samples or historical data are not available during field development stage. Meanwhile, the recommended demulsifers from IOEMS are at 17% lower cost than the incumbent demulsifiers used at fields in Malayia, in addition to 90% manhour reduction from conventional trial and error demulsifier screening in lab. Ultimately, the IOEMS has successfully enabled step-change in oilfield emulsion management via an efficient and reliable scientific based digital platform.