Simple Production Model Research Articles

Choice of model and re‐nesting probability function influences behaviour of avian seasonal productivity models and their demographic predictions

Measuring seasonal productivity is difficult in multi‐brooded species without labour‐intensive ringing studies. Individual‐based (IB) models have been used to estimate seasonal productivity with no direct knowledge of number of nesting attempts, but they are often based on simplified re‐nesting probability (φR) step‐functions instead of observed or more biologically plausible ones. We present a new, open‐source IB seasonal productivity model parameterized from studies of Black Redstart Phoenicurus ochruros and Yellowhammer Emberiza citrinella. We examined how the φR function shape (empirical versus simplified) influenced (1) model performance, (2) re‐nesting compensation and (3) population‐level predictions of a simulated management intervention. Population‐level predictions were made only for Yellowhammer as we had more detailed demographic data, such as survival rates, available. Pattern‐oriented modelling revealed that IB models produced realistic within‐population distributions of breeding parameters, and those specified with an observed or empirically derived φR function generally outperformed those specified with simpler step functions. Strength of re‐nesting compensation differed depending on the φR function used. For Yellowhammers, type of φR function in IB models marginally influenced population‐level predictions of a simulated management intervention (potential population growth rate increased between 23% and 29% relative to no management intervention). In contrast, a simple deterministic productivity model, which did not simulate re‐nesting compensation, predicted a 41% increase in potential population growth. At a population level, choice of φR function may have less influence on IB model predictions, but choice of model itself (IB versus deterministic) may have substantial impact. We discuss how more biologically plausible φR functions might either be observed directly, derived from nest data, or estimated from proxy information such as moult or brood patch changes.

Technology Focus: Formation Evaluation (August 2023)

Fractures, whether natural or hydraulic, serve as crucial pathways for fluid flow within rock formations. Because natural and hydraulic fractures are generated hundreds of meters underground, their parameters always seem to be a black box. Their influence on pressure propagation and well productivity, however, cannot be overstated. So how well are we doing in fracture evaluation and modeling? Fracture evaluation can be regarded as an inverse problem, wherein the structural characteristics of a system are deduced based on input and output signals. Our objective is to ascertain the distribution, orientation, connectivity, and properties of fractures through the mathematical and physical methods applied to field data. Generally, we can use fracture-evaluation techniques such as surface tilt fracture mapping, downhole tilt fracture mapping, microseismic fracture mapping, tracer testing, temperature logs, production logs, borehole image logs, downhole video, caliper logs, production analysis, and well testing. In parallel to fracture evaluation, fracture modeling assumes a computational approach to simulate fractures within subsurface reservoirs. We have various methodologies such as analytical, semianalytical, or numerical approaches to develop fracture models, including dual-porosity models, discrete fracture models, embedded discrete fracture models, and flow-net models. By means of fracture simulations, we can glean valuable insights pertaining to transient pressure behaviors, optimal production schemes, and estimation of ultimate recovery. Despite the significant progress made, a gap still exists between theoretical advancements and practical field application in fracture evaluation and modeling, because underground fractures are often more complex than initially expected and nonunique solutions for fracture evaluation are commonplace. Thus, fracture evaluation and modeling represent complex and interdisciplinary fields, requiring expertise in geology, reservoir engineering, geomechanics, simulation, and related disciplines. We also need continuous research endeavors and advancements in fracture evaluation and modeling techniques to augment our understanding of fracture behavior and reservoir performance in the oil and gas industry, as demonstrated in the selected papers and recommended additional reading. Recommended additional reading at OnePetro: www.onepetro.org. SPE 212296 A Simple Analytical Model for Oil Production From Partially Fractured Reservoirs To Estimate Size of Finite Fracture Networks by Sait I. Ozkaya, Consultant SPE 209624 A Flow-Net-Based Method for History Matching and Production Prediction of Shale or Tight Reservoirs With Fracturing Treatment by Hui Zhao, Yangtze University, et al. SPE 209293 A Hybrid Embedded Discrete Fracture Model and Dual-Porosity, Dual-Permeability Work Flow for Hierarchical Treatment of Fractures in Practical Field Studies by Mun-Hong Hui, Chevron, et al.

Rise and fall of sea ice production in the Arctic Ocean’s ice factories

The volume, extent and age of Arctic sea ice is in decline, yet winter sea ice production appears to have been increasing, despite Arctic warming being most intense during winter. Previous work suggests that further warming will at some point lead to a decline in ice production, however a consistent explanation of both rise and fall is hitherto missing. Here, we investigate these driving factors through a simple linear model for ice production. We focus on the Kara and Laptev seas-sometimes referred to as Arctic “ice factories” for their outsized role in ice production, and train the model on internal variability across the Community Earth System Model’s Large Ensemble (CESM-LE). The linear model is highly skilful at explaining internal variability and can also explain the forced rise-then-fall of ice production, providing insight into the competing drivers of change. We apply our linear model to the same climate variables from observation-based data; the resulting estimate of ice production over recent decades suggests that, just as in CESM-LE, we are currently passing the peak of ice production in the Kara and Laptev seas.

Human Capital Depreciation and Returns to Experience

Human capital can depreciate if skills are unused. But estimating human capital depreciation is challenging, as worker skills are difficult to measure and less productive workers are more likely to spend time in nonemployment. We overcome these challenges with new administrative data on teachers’ assignments and their students’ outcomes, and quasi-random variation from the teacher assignment process in Greece. We find significant losses to output, as a one-year increase in time without formal employment lowers students’ test scores by 0.05 standard deviations. Using a simple production model, we estimate a skill depreciation rate of 4.3 percent and experience returns of 6.8 percent. (JEL I21, J24, J45, J64, J65)

A Simple Analytical Model for Oil Production from Partially Fractured Reservoirs to Estimate Size of Finite Fracture Networks

Summary Most oil reservoirs are partially fractured, characterized by finite fracture networks (FFNs) in a sea of isolated fractures. It is necessary to determine size and shape of each FFN explicitly for reservoir simulation. FFN size is correlated with fracture connectivity, which is a function of fracture density, length, and angular scatter. Oil production from FFNs exhibits a long-term dual-porosity behavior. The initial fast rate (Phase I) represents depletion of matrix within FFN, and the subsequent gradual decline phase represents radial flow from the matrix outside the FFN perimeter. Thus, FFN size can be calculated from the cumulative oil production from Phase I, taking into account the pore volume, oil compressibility, and pressure decline. It is not always possible to identify the dual-porosity behavior by visual inspection. A mathematical model is needed to estimate FFN size. For this purpose, a set of three fundamental equations are derived for production rate, cumulative production, and pressure as a function of time. The model is a modified and simplified version of material balance equations with easy analytical solution. It is designed for fractured reservoirs with layer-bound fractures. Production is single-phase black oil under depletion drive. The analytical model was tested on four vertical wells. The unknown parameters such as FFN size, size of well drainage area, and fracture aperture are adjusted until an optimum fit to actual production data is obtained. FFN elliptical shape is estimated from average fracture strike and strike standard deviation. The results are validated by FFN size, fracture length, and aperture measurements from borehole images. The results are approximate but sufficient for preliminary mapping of FFNs with location and size and other critical attributes including fracture drainage area, matrix block size, fracture aperture, and permeability in partially fractured reservoirs.

Matching intermittent electricity supply and demand with electricity storage - An optimization based on a time scale analysis

The rising share of Variable Renewable Energy Sources (VRES) in the electricity generation mix leads to new challenges for the whole energy system. It especially raises technological issues to handle variability and to match electricity load with supply at all times. This study introduces a new methodology to quantify the relevance of different electricity storage technologies, based on a time scale analysis. It additionally provides an understanding of how electricity storages work in combination to handle variable load and intermittent generation. First, we set up a simple model of variable production, fluctuating over a single time-scale. This analysis provides figures of merit for electricity storage and curtailment. Second, we simulate the collaboration and competition behavior of various storages with a dual time-scale signal. Then, results are compared with the optimization of an energy system with real variable electricity supply and consumption time-series. We eventually highlight the trade-off mechanisms between the storage efficiency and its investment cost.

The effect of distal‐end trimming onSaccharina latissimamorphology, composition, and productivity

AbstractAs kelp cultivation increases around the world, so does the need for farm management strategies that produce specific crop characteristics, optimize yield, widen harvesting windows, and prevent biomass loss. Distal‐end trimming of macroalgae has been recommended as a farm management method addressing these needs. In this study, we trimmed cultivatedSaccharina latissimasporophytes grown in the Western Gulf of Maine (WGoM) to 60 cm above the stipe–blade interface. We characterized the effect of trimming on the morphology, tissue nutrient content, stable isotope ratio, and nitrate reductase activity of the kelp. We also evaluated the economic trade‐offs of trimming using a simple production model. The results suggest that trimming the blade to 60 cm may have minimal biological consequences. Additionally, the trimming appears to benefit “short” kelp blades in proximity to the trimmed blades. Daily yield (% increase in weight day−1) after trimming was initially lower than the control, but late‐season daily yields and crop‐retention following storms were markedly improved. Ultimately, we conclude that growers could use trimming to acquire kelp biomass earlier in the season, retain late‐season biomass, and potentially increase the total revenue gained from kelp farming if price premiums can be exacted for this biomass.

Changes in risk preferences: Evidence from Swedish harness horse racing data

We measure the time variation of risk preferences in real market data. We utilize data on Swedish tote-betting on horse races for the period 1995 to 2015 and show that risk preferences among horse-race bettors change with economic conditions. More specifically, we extract a measure of risk-aversion based on the favorite-longshot bias (FLB) and provide evidence that the computed measure follows the consumer-confidence index. In addition, we show by an application that the FLB-based risk-preference measure sharpens the predictions of a simple forecasting model for Swedish industrial production. Furthermore, we show that risk-aversion consistently increases following shocking news on disastrous events, including non-economic events such as natural disasters and terrorist attacks. We argue that emotions, such as fear, are the likely explanation for this variation.

Simulation of simple 2D plasma jet model for NO, OH, and H2O2 production via Multiphysics in laminar flow and transport of diluted species through design of experiment method

The plasma jet technique, a popular method for generating reactive oxygen and nitrogen species through an inert gas (such as Ar) mixed with air, was investigated. A plasma jet model was developed from a selection of statistical data, and the resulting NO, OH, and H2O2 concentrations were examined. The objective of the study was to establish a simple 2D plasma jet module and to mathematically understand the involved chemical reactions through the Multiphysics (finite element method) program. Determination of optimized conditions via the design of experiment method was performed. To create new responses, three nominal concentrations (NO, OH, and H2O2) were used to measure the performance of the species product. A full factorial design based on two levels, or 23 runs, with three central points and two replications was employed in the simulations using COMSOL Multiphysics 5.3a software. The main effects and interactions between the variables were identified for three main parameters: gas velocities of 40–70 m/s, plasma gaps of 10–30 mm, and simulation times of 2.8–4 ms. These parameters were selected to unravel design possibilities with external variables, which can significantly contribute to the process of designing a prototype of a cell-scaled plasma jet model.

Supply Chain Resilience: Should Policy Promote Diversification or Reshoring?

Supply chain disruptions, which have become commonplace, are often associated with globalization and trade. Little is known about optimal policy in the face of insecure supply chains. Should governments promote resilience by subsidizing backup sources of input supply? Should they encourage firms to source from closer and presumably safer domestic suppliers? We address these questions in a very simple model of production with a single critical input and with exogenous risks of relationship-specific and country-wide supply disturbances. We follow Matsuyama and Ushchev (2020) in positing a class of preferences that are homothetic with a single aggregator and that obey Marshall's Second Law of Demand. The familiar case of CES preferences is a member of the class, but it imposes restrictions that are important for policy conclusions.We find that, in the CES case, a subsidy for diversification achieves the constrained social optimum and dominates a policy that promotes reshoring or offshoring. When the demand elasticity rises with price, two policy instruments generally are needed to achieve efficient supply chains, private investments in resilience may be socially excessive, and policy that alter incentives to invest at home versus abroad may achieve greater welfare than ones that encourage or discourage diversification.

Credit and investment distortions: Evidence from Mexican manufacturing

We document a transmission channel from credit conditions to capital accumulation via investment wedges. Using a simple multi-industry model of production and investment, we measure these wedges at the 4-digit industry level from Mexican manufacturing and show that they account for most of the changes in aggregate capital over time. We also find a robust relation between the wedges and financial variables: credit and interest rates, also measured at the industry level.

Human Capital Depreciation

Human capital can depreciate if skills are unused. But estimating human capital depreciation is challenging, as worker skills are difficult to measure and less productive workers are more likely to spend time in non-employment. We overcome these challenges with new administrative data on teachers’ assignments and their students’ outcomes, and quasi- random variation from the teacher assignment process in Greece. We find significant losses to output, as a one-year increase in time without formal employment lowers students’ test scores by 0.09 standard deviations. Using a simple production model, we estimate a skill depreciation rate of 4.3% and experience returns of 6.8%.

A simple empirical model for blood platelet production and inventory management under uncertainty

The purpose of this study is to develop a pragmatic method for managing the inventory and production of blood platelets in places with inappropriate infrastructure. Thus far, we can find a rich number of papers regarding the optimization of blood products supply chain but most of them are impractical due to utilizing so many mathematical formulas and parameters. Hence, as an interdisciplinary study, we should develop a comprehensible method for medical workers and doctors to optimize the supply chain, maintain the quality of services and overcome the challenges. The inventory manager has to cope with multifaceted problems, among those are limited availability of donors, the uncertainty of demand, maintaining the quality and quantity of the products at a reasonable level and on-time response to medical centers and finally yet importantly avoid waste caused by overproduction. To tackle these problems, we employed Markov decision process and simulation to ensure the accountability of the model. Eventually, the real managerial insight provided through gathering data regarding the number of casualties caused by road accidents in Semnan province, Iran, and the number of blood platelet ordered by the hospitals and coordination between medical centers and the Blood Transfusion Center. The results indicate the accessibility of the model by inventory manager and physicians in the transfusion center and the reduction of waste due to appropriate production planning.

Fisheries for the future: greenhouse gas emission consequences of different fishery reference points

Abstract Global fisheries have for long been scrutinized in terms of ecosystem effects but only more recently for their greenhouse gas emissions. These emissions are dominated by fuel use on fishing vessels and the levels are often neglected side effects of resource overexploitation. Using a simple production model, Pella-Tomlinson, we illustrate how fuel efficiency (fuel use per unit of catch) varies with the level of exploitation and biomass depletion. For this model, fuel use per unit catch rises hyperbolically with fishing effort—it is relatively flat at low levels of effort but rises steeply as effort increases and biomass and catch decline. In light of these findings, the general fuel efficiency relationship with common fishery reference points on stock status is discussed, as well as other means of reducing fuel use and thus greenhouse gas emissions. We conclude that much may be gained by considering fuel efficiency in setting reference points for target stock biomass in fisheries and encourage further investigations.

The Surprisingly Low Carbon Mass in the Debris Disk around HD 32297

Abstract Gas has been detected in a number of debris disks. It is likely secondary, i.e., produced by colliding solids. Here, we report ALMA Band 8 observations of neutral carbon in the CO-rich debris disk around the 15–30 Myr old A-type star HD 32297. We find that C0 is located in a ring at ∼110 au with an FWHM of ∼80 au and has a mass of (3.5 ± 0.2) × 10−3 M ⊕. Naively, such a surprisingly small mass can be accumulated from CO photodissociation in a time as short as ∼104 yr. We develop a simple model for gas production and destruction in this system, properly accounting for CO self-shielding and shielding by neutral carbon, and introducing a removal mechanism for carbon gas. We find that the most likely scenario to explain both C0 and CO observations is one where the carbon gas is rapidly removed on a timescale of order a thousand years and the system maintains a very high CO production rate of ∼15 M ⊕ Myr−1, much higher than the rate of dust grind-down. We propose a possible scenario to meet these peculiar conditions: the capture of carbon onto dust grains, followed by rapid CO re-formation and rerelease. In steady state, CO would continuously be recycled, producing a CO-rich gas ring that shows no appreciable spreading over time. This picture might be extended to explain other gas-rich debris disks.

Human Capital Depreciation

Human capital can depreciate if skills are unused. But estimating human capital depreciation is challenging, as worker skills are difficult to measure and less productive workers are more likely to spend time in non-employment. We overcome these challenges with new administrative data on teachers’ assignments and their students’ outcomes, and quasi- random variation from the teacher assignment process in Greece. We find significant losses to output, as a one-year increase in time without formal employment lowers students’ test scores by 0.09 standard deviations. Using a simple production model, we estimate a skill depreciation rate of 4.3% and experience returns of 6.8%.

Human Capital Depreciation

Human capital can depreciate if skills are unused. But estimating human capital depreciation is challenging, as worker skills are difficult to measure and less productive workers are more likely to spend time in non-employment. We overcome these challenges with new administrative data on teachers’ assignments and their students’ outcomes, and quasi- random variation from the teacher assignment process in Greece. We find significant losses to output, as a one-year increase in time without formal employment lowers students’ test scores by 0.09 standard deviations. Using a simple production model, we estimate a skill depreciation rate of 4.3% and experience returns of 6.8%.

Ecology of Pseudodiaptomus annandalei in tropical aquaculture ponds with emphasis on the limitation of production

ABSTRACT The calanoid copepod Pseudodiaptomus annandalei is used as live feed in aquaculture because of its nutritional value and the ability to cope with environmental fluctuations in outdoor ponds. However, little knowledge exists on its ecology. Here we investigated the ecology of P. annandalei in an aquaculture pond in Vietnam. Temperature, salinity, chlorophyll a and biomass of protozoans and copepods were monitored every other day for 1 month. Experiments on protozoan growth and grazing by P. annandalei were also conducted. Copepod fecal pellet production and temperature-dependent egg hatching rates were likewise quantified. Despite very high phytoplankton biomass, biomass of P. annandalei was surprisingly low. Copepod production was estimated from three independent methods: clearance, weight-specific egg production rate (SEP) and specific fecal pellet production rate. SEP proved to be accurate to predict the in situ population growth in the pond. A simple model for production of P. annandalei based on SEP was developed. Our study extends our knowledge of how environmental conditions in the pond may affect the population dynamics and production of copepods. The results have important implications for pond managements ensuring stable copepod production and harvest.

Evaluation of productive biofilms for continuous lactic acid production

In white biotechnology research, the putative superiority of productive biofilms to conventional biotransformation processes based on planktonic cultures has been increasingly discussed in recent years. In the present study, we chose lactic acid production as a model application to evaluate biofilm potential. A pureculture of Lactobacillus bacteria was grown in a tubular biofilm reactor. The biofilm system was cultivated monoseptically in a continuous mode for more than 3 weeks. The higher cell densities that could be obtained in the continuous biofilm system compared with the planktonic culture led to a significantly increased space-time yield. The productivity reached 80% of the maximum value 10 days after start-up and no subsequent decline was observed, confirming the suitability of the system for long-term fermentation. The analysis of biofilm performance revealed that productivity increases with the flow velocity. This is explained by the reduced retention time of the liquid phase in the reactor, and, thus, a minor pH drop caused by the released lactic acid. At low flow velocities, the pH drops to a value where growth and production are significantly inhibited. The biofilm was visualized by magnetic resonance imaging to analyze biofilm thickness. To deepen the understanding of the biofilm system, we used a simple model for cell growth and lactic acid production.

Modelo bayesiano de producción excedente con autocorrelación serial

Se presenta un modelo simple de producción excedente al que se denomina Modelo de Producción Excedente con Autocorrelación Serial (MPECAS) debido a que considera como único supuesto que la producción excedente presenta correlación serial y no tiene una relación funcional explícita con la biomasa. Su aplicación se logra solo con un índice de abundancia proporcional a una potencia dada de la abundancia media real del recurso y la serie de capturas anuales correspondientes. La estimación de los parámetros del modelo se plantea en un contexto bayesiano utilizando el algoritmo SIR (Sampling Importance Resampling). Se proponen criterios de riesgo sencillos para estimar la Captura Máxima Biológicamente Aceptable (CMBA) y los riesgos asociados a cada nivel de captura hipotética considerada. Se llevó a cabo un ejercicio de simulación para evaluar la capacidad estadística del MPECAS para reproducir la información proporcionada por un modelo operacional de producción excedente de Schaefer considerado como real. Finalmente, se presenta un ejemplo de aplicación con el recurso corvina rubia (Micropogonias furnieri) y se muestran las CMBA para el 5 y 10% de riesgo de disminución de biomasa en el año siguiente al de evaluación calculadas con el modelo de Schaefer y el MPECAS.
 † El Lic. Daniel R. Hernández falleció el 25 de enero de 2019.