Products, forecasting

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. 

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. 

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. 

Petroleum Engineering Reserves Production forecasts - oil, sales gas... 

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). 

Material Control. Production forecasting, scheduling, direct and iadirect material procurement, purchasiag, shipping and receiving, storerooms, storage, surplus equipment, and reclamation of materials are iacluded. 

Ball and roUer bearings represent the largest business segment with worldwide production estimated at 14 biUion in 1988 (1). U.S. production, forecast for 3.6 biUion in 1991, has fallen 5% aimuaHy for several years (2). This decrease is attributed largely to the slump in the automotive industry which represents 31% of the market for rolling-element bearings (3). 

Campbell, C. J. (1997). The Coming Oil Crisis. Brentwood, United.Kingdom Multi-Science Publishing Company. Edwards, J. D. (1997). Crude Oil and Alternate Energy Production Forecasts for the Twenty-first Centuiy The End of the Hydrocarbon Era. American Association of Petroleum Geologists Bulletin 81 1292-1305. 

The definitions above are an abbreviated version of those used in a veiy complex and financially significant exercise with the ultimate goal of estimating resei ves and generating production forecasts in the petroleum industry. Deterministic estimates are derived largely from pore volume calculations to determine volumes of either oil nr gas in-place (OIP, GIP). This volume when multiplied by a recovery factor gives a recoverable quantity of oil or natural gas liquids—commonly oil in standard barrels or natural gas in standard cubic feet at surface conditions. Many prefer to use barrels of oil equivalency (BOE) or total hydrocarbons tor the sum of natural gas, natural gas liquids (NGL), and oil. For comparison purposes 6,000 cubic feet of gas is considered to be equivalent to one standard barrel on a British thermal unit (Btu) basis (42 U.S. gallons). 

Campbell, C. J. (2006). Regular Conventional Oil Production to 2100 and Resource Based Production Forecast. (August 2006). www.oilcrisis.com/campbell. 

Figure 7 shows expected coke production levels in the United States by sulfur content category. Shown is Pace s current petroleum coke production forecast. Most of the additional coke production will be in the category of four percent sulfur or greater. 

Phase 4 follows development. This book only considers the exploitation phase in as far as it influences development - not the daily operation of a company. The subjects that we will consider are how to organize the marketing of the product, forecasting costs and revenues (the... 

RDA Recommended Daily Allowance (US Food and Nutrition Board) receptor site in an organ, a cell or a macromolecule at which active substances (including toxic substances) are bound reserves the quantity of resources which can be economically exploited using the currently available processes reservoir storage container, in environmental chemistry a natural receptacle from which the outflow of material per unit time is small compared with its total capacity resource reserve source of supply, geological the natural content of raw materials in the Earth s crust which are actually or potentially suitable for extraction and production (forecasts also include the marginal resources) - even under changed economic circumstances... 

Production forecasting for each fine item and its patterns is not often available. 

From the materials point of view, we have clearly seen that both the total polyethylene and the polypropylene industries are still on an ascending curve, far away it seems from a plateau in terms of growth. This is clear from production forecast data in Figs. 2.2 and 2.3 discussed earlier in this chapter. 

The story of iron takes us back to the period of the Hittite Empire around 1300 BC, when iron started to replace bronze as the chief metal used for weapons and tools. Until today the stoiy remains uncompleted and the social and economic impact of the iron and steel industry is now beyond imagination. In the year 2005 1.13 billion tons of crude steel were produced. Compared to 2004 this is an increase of 6.8%. That same year the steel production in China increased from 280.5 to almost 350 milhon tons. Concerning stainless steel according to the International Stainless Steel Forum (ISSF), the global production forecast for 2006 now stands at 27.8 million metric tons of stainless erode steel, up 14.3% compared to 2005. 

A forecast is not a forecast is not a forecast. As companies work on demand architectures, they will find that they have multiple forecasts—sales forecast, financial forecast, production forecast, supply chain forecast, and procurement forecast—each with a different data model, granularity, and bias. As a result, tight integration is not a good idea and the so-called one-number forecast is not realistic. Instead, as companies work through the issues, they will find the need to model market demand in a ship to or channel data model, and translate this demand to a ship from data model. The sales forecast then becomes an input into the corporate forecast, and this corporate forecast becomes the input into the financial forecast. These concepts require education and are often a major change management issue. 

Item segmentation by product forecastability helps companies to achieve greater accuracy in their product forecasting processes. An assessment helps to pinpoint the issues. The framework in Figure 3.5 is a useful way to segment products and apply the concepts to supply chain design. 

The proposed method for providing decision support with respect to an optimal maintenance strategy for ageing systems is in principle a performance forecasting study for different relevant scenarios to compare the effect of different maintenance related decisions. However, some additional parameters are required as input compared to a regular production forecasting study, as discussed in Section 3.1. The different scenarios may include ... 

Whether the NPV or the production availability is the main output, it should be presented as a function of time. In regular production forecasting, the production availability or NPV is often the main output which is presented as an overall average. In an ageing system, we generally experience deterioration such that the production availability decreases with time. 

In this section, it will be performed a literature review for each one of the six categories of Product Lifecycle management - New Product Forecast, Supply chain Approach for New Product, Risk Assessment and Management, Product Tracking Visibility, Portfolio Optimization, Senior Management Support. This review allowed identify the DDSC characteristics for each category which was used to develop the five level maturity model. 

New product forecast is an important capability to guarantee product availability in the early phases of introduction in the market. However, benchmarking research shows that new product forecast accuracy is only slightly above 50% on average 1 year after the launch. 

Kahn (2006) provides direction on how new product forecasting should be performed. He states that the first step is to establish the forecasting objective, as this will clarify the purpose and intent of the forecast so that a meaningful forecast can be made. Once the forecasting objective is established, consideration is needed regarding the forecasting level, time horizon, interval and form. 

Forecasting level refers to the focal point in the corporate hierarchy where the new product forecast applies. Common levels include the stock keeping unit (SKU) level, stock keeping unit per location (SKUL), product line, strategic business unit (SBU) level, company level, and industry level. 

Forecasting time horizon refers to the time frame for how far out one should forecast. New product forecasts may correspond to a single point in the future or a series of forecasts extending out for a length of time. Examples include a 1-2 year time horizon for most fashion products, 2-5 years for most consumer products goods, and ten-plus years for pharmaceutical products. 

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