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Forecast/forecasting

Almost anyone who can extrapolate trends can make forecasts. Forecasts... [Pg.218]

Demand can be estimated using forecasting. Forecasting is a necessary prerequisite for many of the methods and procedures used in operations management (Lewis, 1981, p. 241). Forecasting demand for goods and services requires the use of information, mathematical functions, and statistical analyses. [Pg.74]

Communicate, Duplication of forecasting effort Mistrust of the official forecast Little understanding of Establish crossfunctional approach to forecasting Establish independent forecast group that sponsors cross- All relevant information used to generate forecasts Forecasts trusted by users Islands of analysis... [Pg.52]

Period Actual Demand Forecast Forecast Error Absolute Error ... [Pg.116]

Based on these models several forecasting systems are commercially available in the market such as Predicast of Aperia, SAP Demand and Forecasting, Forecast Management by Demand Solutions and Optimate of D3S (Thomassey, 2010). [Pg.110]

High customer satisfact on Accurate forecasting (forecasting methods) Satisfactory Lead translt time Appropriate inventory segmentation (sufficient visibilitv) Sufficient prodi ction capacities... [Pg.266]

Error Estimates for Tahoe Salt Forecasting Forecasting Method MAD MAPE (%) TS Range... [Pg.202]

Actual) (Eorecasts) Change (Eorecast) (Eorecast) (Eorecast) Change (Actual) (Forecast) (Forecast) Change... [Pg.11]

Keywords compressibility, primary-, secondary- and enhanced oil-recovery, drive mechanisms (solution gas-, gas cap-, water-drive), secondary gas cap, first production date, build-up period, plateau period, production decline, water cut, Darcy s law, recovery factor, sweep efficiency, by-passing of oil, residual oil, relative permeability, production forecasts, offtake rate, coning, cusping, horizontal wells, reservoir simulation, material balance, rate dependent processes, pre-drilling. [Pg.183]

This section will consider the behaviour of the reservoir fluids in the bulk of the reservoir, away from the wells, to describe what controls the displacement of fluids towards the wells. Understanding this behaviour is important when estimating the recovery factor for hydrocarbons, and the production forecast for both hydrocarbons and water. In Section 9.0, the behaviour of fluid flow at the wellbore will be considered this will influence the number of wells required for development, and the positioning of the wells. [Pg.183]

In contrast to an oil production profile, which typically has a plateau period of 2-5 years, a gas field production profile will typically have a much longer plateau period, producing around 2/3 of the reserves on plateau production in order to satisfy the needs of the distribution company to forecast their supplies. The Figure 8.9 compares typical oil and gas field production profiles. [Pg.194]

The production profile for oil or gas is the only source ofrevenueior most projects, and making a production forecast is of key importance for the economic analysis of a proposal (e.g. field development plan, incremental project). Typical shapes of production profile for the main drive mechanisms were discussed in Section 8.2, but this section will provide some guidelines on how to derive the rate of build-up, the magnitude and duration of the plateau, the rate of decline, and the abandonment rate. [Pg.208]

Within the project box, the cashflow oi the project (or other investment opportunity) is the forecast of the funds absorbed and the money generated during the project lifetime. Take, for example, the development of an oil field as the investment opportunity. Initially the cashflow will be dominated by the capital expenditure (capex) required to design, construct and commission the hardware for the project (e.g. platform, pipeline, wells, compression facilities). [Pg.305]

Petroleum Engineering Reserves Production forecasts - oil, sales gas... [Pg.306]

Corporate Planning Forecast oil and gas prices Discount rates, hurdle rates Exchange rates Inflation forecast Market factors Political risk, social obligations... [Pg.306]

The capital cost estimates are generated by the Engineering function, often based on 50/50 estimates (equal probability of cost overrun and underrun). It is recommended that the operating expenditure is estimated based on the specific activities estimated during the field lifetime (e.g. number of workovers, number of replacement items, cost of forecast manpower requirements). In the absence of this detail it is common, though often inaccurate, to assume that the opex will be composed of two elements fixed opex and variable opex. [Pg.308]

The reservoir model will usually be a computer based simulation model, such as the 3D model described in Section 8. As production continues, the monitoring programme generates a data base containing information on the performance of the field. The reservoir model is used to check whether the initial assumptions and description of the reservoir were correct. Where inconsistencies between the predicted and observed behaviour occur, the model is reviewed and adjusted until a new match (a so-called history match ) is achieved. The updated model is then used to predict future performance of the field, and as such is a very useful tool for generating production forecasts. In addition, the model is used to predict the outcome of alternative future development plans. The criterion used for selection is typically profitability (or any other stated objective of the operating company). [Pg.333]

Market forces determine the demand for a product, and the demand will be used to forecast the sales of hydrocarbons. This will be one of the factors considered by some governments when setting the production targets for the oil company. For example, much of the gas produced in the South China Sea is liquefied and exported by tanker to Japan for industrial and domestic use the contract agreed with the Japanese purchaser will drive the production levels set by the National Oil Company. [Pg.346]

Forecasting of time series behavior using lead time data (data obtained during current experiment) for prediction of the material response to the similar actions and loads in future or of testing results for twin material specimens during lead time . [Pg.188]

Standard procedures that are used for testing of construction materials are based on square pulse actions or their various combinations. For example, small cyclic loads are used for forecast of durability and failure of materials. It is possible to apply analytical description of various types of loads as IN actions in time and frequency domains and use them as analytical deterministic models. Noise N(t) action as a rule is represented by stochastic model. [Pg.189]

Nesvijski, E.G., Nogin, S.I. Acoustic Emission Technics for Nondestructive Evaluation of Stress of Concrete and Reinforced Concrete Structures and Materials. Third Conference on Nondestructive Evaluation of Civil Structures and Materials, Boulder, CO, 1996. Nesvijski, E. G. Failure Forecast and the Acoustic Emission Silence Effect in Concrete. ASNT s Spring Conference, Houston, TX, 1997. [Pg.193]

BE2-0945 Intelligent forecasting system for refineries and power systems Dr.B. Bitzei Uftl9- 0SKimtnoch6chule Paderbom... [Pg.936]

Although the rapid cost increases and shortages of petroleum-based feedstocks forecast a decade ago have yet to materialize, shift to natural gas or coal may become necessary in the new century. Under such conditions, it is possible that acrylate manufacture via acetylene, as described above, could again become attractive. It appears that condensation of formaldehyde with acetic acid might be preferred. A coal gasification complex readily provides all of the necessary intermediates for manufacture of acrylates (92). [Pg.156]

Usage Actual 1982 1987 Forecast, 1992 Average aimual growth rate, 1987-1992,%... [Pg.516]

Major Chlorine Markets. Forecasted changes in chlorine consumption (Table 23) are addressed below in descending order of the importance of the major derivative, based on 1987 demand. [Pg.517]

Titanium Tetrachloride. The major use for titanium tetrachloride [7550 5-0] is in titanium dioxide production, and titanium dioxide [13463-67-7] is enjoying strong growth for use as a filler in pulp and paper manufacture and as a pigment in paint and plastic manufacture. Annual growth for this product is forecasted at between 2.5 and 3.0% through 1992. [Pg.517]

Cellulosics. Rayon and other cellulose products such as cellophane and cellulose ethers (qv) consume 1.9% of U.S. caustic soda demand. Because of competitive products, however, this market has been decreasing since 1965 and forecasted average annual growth through 1992 is less than 0.4% (6) (see Cotton). [Pg.518]

Caustic Soda to Chlorine Balance. In 1988, the ratio of U.S. caustic soda to chlorine consumption was 0.96 1 (see Fig. 39). Since 1968 this ratio has ranged from alow of 0.88 1 (1978 and 1981) to a high of 0.98 1 (1969). No single factor can explain these variations, since caustic soda and chlorine, with few exceptions, have different markets and are therefore not driven by the same economic forces. This ratio is expected to trend upward over the next five years, however, since caustic soda consumption in the United States is forecasted to grow somewhat faster than chlorine consumption. It is expected that this ratio will remain within the range experienced in 1970—1990. Because caustic soda is co-produced with chlorine at a theoretical ratio of 1.1 1, a U.S. consumption ratio below that level results in excess avaHabihty of caustic soda. This material is typically shipped offshore to fill a significant export demand, and in 1988, for example, net U.S. exports of caustic soda amounted to 7.1% of production. [Pg.518]

EOY speeds are the most recent development in PET spinning (78). Properties are similar to HOY and appear to be limited by the differential cooling rate from filament surface to filament core. This leads to radial distribution of viscosity, stress, and, consequentiy, molecular orientation (75). Eiber tensde strength is limited. Nevertheless, speeds up to 7000 m /min are commercial and forecasts are for speeds up to 9000 m /min by the year 2000 (79). Speeds to 9000 m/min have been studied (68,80,81). [Pg.330]


See other pages where Forecast/forecasting is mentioned: [Pg.776]    [Pg.171]    [Pg.9]    [Pg.65]    [Pg.462]    [Pg.178]    [Pg.206]    [Pg.304]    [Pg.307]    [Pg.308]    [Pg.326]    [Pg.328]    [Pg.345]    [Pg.187]    [Pg.193]    [Pg.193]    [Pg.791]    [Pg.913]    [Pg.914]    [Pg.276]    [Pg.118]    [Pg.516]    [Pg.517]    [Pg.517]    [Pg.517]    [Pg.517]    [Pg.518]    [Pg.518]    [Pg.518]    [Pg.126]    [Pg.130]    [Pg.286]    [Pg.439]    [Pg.165]   


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AMMONIA PRODUCTION, CONSUMPTION, AND FORECASTS

ARIMA forecasting

Adaptive forecasting

Adaptive forecasting model) method

Aggregate demand forecast

Aggregate forecasts

Air pollutants forecasting

Air pollution forecasts

Air quality forecasting

Annual forecasting

Assessing forecasting performance

Basic Approach to Demand Forecasting

Buyer Forecasting Processes Commonly Used

Buyer forecasting processes

CPFR (Collaborative Planning, Forecasting, and

Calculation and Forecast of the Sea State

Calculation of Forecasting Trend Value

Capacity planning Forecasting

Case study demand forecasting

Causal forecasting methods

Characteristics of Forecasts

Chemical weather forecasting

Coastal weather forecasts

Collaboration Planning, Forecasting, and Replenishment)

Collaborative Planning Forecast and

Collaborative Planning Forecast and Replenishment

Collaborative Planning, Forecasting and Replenishment (CPFR)

Collaborative Planning, Forecasting, and

Collaborative Planning, Forecasting, and Replenishment

Collaborative forecasting

Collaborative planning, forecasting

Combined Forecasting and Determining Weights Method

Components of a Forecast and Forecasting Methods

Consensus forecasts

Constant Level Forecasting Methods

Corrosion Forecast

Data driven forecast

Demand Forecasting Dynamic Equation Model

Demand exceeding forecast

Demand forecast

Demand forecasting

Demand forecasting factors influencing

Demand management Forecasting

Demand management statistical forecast

Determination of Forecasting Model

Ecological forecasting

Elastic Forecast

Electronic collaboration forecasts

Emission forecasting

Emission forecasting example

Emission forecasting plants

Energy consumption, forecast

Enhanced forecasts at several stages of production

European Centre for Medium-Range Weather Forecasts

Exponential forecasting

Exponential smoothing, forecasting

Exponential smoothing, forecasting method

Fashion sales forecasting

Fashion sales forecasting experiments

Fashion sales forecasting learning machines

Fillers forecasting

Flood events forecasting

Forecast Accuracy Can Be Improved

Forecast History Data Selection

Forecast Money Flows

Forecast Underpinnings

Forecast accuracy

Forecast driven

Forecast error measurement

Forecast error measures

Forecast errors

Forecast evaluation

Forecast evolution

Forecast for capacity, execute against demand

Forecast hydrogeochemical

Forecast of Chemical Resistance Coefficient

Forecast of Commercialization

Forecast operational

Forecast process

Forecast state

Forecast/forecasting adaptive

Forecast/forecasting aggregate

Forecast/forecasting characteristics

Forecast/forecasting collaborative

Forecast/forecasting components

Forecast/forecasting demand

Forecast/forecasting error

Forecast/forecasting horizon

Forecast/forecasting long-term

Forecast/forecasting methods

Forecast/forecasting objective

Forecast/forecasting revenue management

Forecast/forecasting supply chain coordination

Forecastable demand

Forecasting

Forecasting

Forecasting Errors

Forecasting Final Subcontract Cost

Forecasting Is a Circular Process

Forecasting Is the Achilles Heel

Forecasting Model Error Estimation and Hypothesis Testing

Forecasting Process

Forecasting Software

Forecasting capabilities

Forecasting error distribution

Forecasting evolution

Forecasting for Multiple Periods

Forecasting forecast value added

Forecasting high-detail

Forecasting improving accuracy

Forecasting in Practice

Forecasting in Practice Survey Results

Forecasting integration with operations

Forecasting management

Forecasting market-driven demand

Forecasting model, network demand

Forecasting needs

Forecasting needs methods

Forecasting performance assessment

Forecasting planning Demand management

Forecasting prices

Forecasting process steps

Forecasting with ARIMA

Forecasts

Forecasts

Forecasts of Future Oil Price Shocks

Fuel Cell Forecasts

Fuels prices, forecasted

Future opportunities forecasts

Global Market Forecasts

Group-Based Forecasting Methods

How Are Needs Forecasted

Hydrogeochemical forecasting

Incorporating Seasonality in Forecasting

Inventory management demand forecasting

Joint forecasting

Linear regression, forecasting method

Long-term forecasts

Market Size and Forecast

Market demand, computer forecasting

Markets, forecasting

Measures of Forecast Error

Methods of Forecasting

Model Forecasting Method

Models for Forecasting, Demand Management, and Capacity Planning

Monitoring Forecast Accuracy

Monthly forecasting

Monthly forecasting Category

Moving average, forecasting method

Multi-Period Forecasting under Constant Level

Multi-Period Forecasting with Seasonality

Multi-Period Forecasting with Seasonality and Trend

Multi-Period Forecasting with Trend

Naive forecast

Naive, forecasting method

Objective, of forecasting

Ozone forecasts

Period forecast

Period forecast base

Plastics growth forecasts

Polyethylene growth forecasts

Prediction forecast

Price data forecasting

Price forecasting model

Prices, computer forecasting

Primary forecast

Products, forecasting

Qualitative forecasting methods

Quantitative Forecasting Methods

Quarterly forecasting

Quarterly forecasting Category

Recent US and Global Forecasts

Reliability of Model Forecasting Results

Resins, growth forecasts

Role of Demand Forecasting in Supply Chain Management

Rubber forecasts

Safety Forecasting

Sales forecasting

Sales forecasting management

Scenario Generation The Forecasting Module

Short-range forecast

Shrinkage forecast

Simulation forecasting methods

Single-point forecast

Solar forecast

Statistical forecast

Statistical forecast accuracy improvement

Statistical forecast accurate forecasts

Statistical forecast evaluation

Statistical forecast fitting model

Statistical forecast sales forecasting

Statistical forecast variability

Statistical forecasting

Summary and Forecast

Summary, Assessment, and Forecast

Supply forecasting

Tahoe Salt forecasting demand

The Role of Forecasting in a Supply Chain

The Role of IT in Forecasting

Time Series Forecasting

Time-series forecasting methods

Transportation forecast rates

Trending and Forecasting

Types of Forecasting Software

United States demand forecast

Using Recent Observed Data to Improve Forecasts

Weather Research Forecast model with

Weather Research Forecast model with Chemistry

Weather forecasting

Weather forecasts

Widget sales forecast

World energy demand forecast

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