Forecast Techniques for Lifting Cost in Gas and Oil Onshore Fields
Authors: Martinez Ricardo E. 
Published: December 2007

Abstract
Forecasting is a technique that helps to predict what will happen in the future, a very useful element in the planning process. There are quantitative techniques to forecast the future with and without historical data. This paper shows the techniques used to forecast lifting cost in new and existing developments of onshore gas and oil fields.
The applied model allows us to predict the evolution of fixed and variable costs during the lifecycle of a field, and to forecast project profits according to different scenarios or development options, so a decision can be made. The cost model developed applies to upstream lifting cost. This model has been validated in fields operated by Perez Companc, with a wide range of development alternatives and maturity.

Introduction
It is imperative to have a model for forecasting lifting cost (production costs) for strategic planning and represent the development options of oil and gas fields. An incorrect estimation of cost could result in poor decisions.
Generally, lifting cost is not assumed to be constant in time, neither in absolute terms ($), nor in unitary terms ($/B.O.E.). Six producing onshore oil and gas fields, operated by Perez Companc in Argentina, have been the source of historical data (from 1995 to present) for this analysis. Table 1 shows the main characteristics of these fields.
We have formulated a numeric model, which intends to predict the variations of lifting cost with time along the exploitation life, starting the modeling process with the identification of field-cost drivers. Three quantitative techniques have been used to test the model against the historical data. All three of them give comparable results and can be used in a complementary way.
A consolidated solution, a system of equations, can be derived reflecting the three techniques. This equations show lifting cost, broken down into variable (with activity level) and fixed (with activity level) costs and allow to identify cost-reduction opportunities.
The hypothesis:Each case can be represented by an unique numeric model. In this model, all the cost drivers are represented by quantitatively defined parameters. There are mathematical formulas that represent the relationships between these parameters.Reserves are given. Cost extrapolations are based on proven developed reserves only, and these are not a variable parameter of the model. This method applies to cases where the end of the cycle is set by the concession permit.Cost extrapolations assume that there will be no technological improvements.Cost extrapolations assume that no new personnel will be hired.It is assumed that all the fields are operated by contractors who use the same philosophies, strategies and techniques of work.The opportunities of cost reduction are variations of the fixed (with activity level) costs by changing the organization, adjustment of own personnel or contractors count.It is assummed that all cases are dealt with the same integrated enviromental protection, safety and health management.Lifting cost does not include neither transportation, nor storage fees.Lifting cost does not include depreciaton, overhead or royalties.Lifting Cost is what the Financial Accounting Standards Board1 defines as production cost (FASB 19).