The initial portion of this paper is reprinted from THE JOURNAL OF CANADIAN PETROLEUM TECHNOLOGY, October-December, 1966, Montreal. The addendum was prepared for presentation with the paper at the SPE Fourth Annual Eastern Regional Meeting to be held in Pittsburgh, Pa., Nov. 2–3, 1967. Permission to publish any portion of this paper must be secured from the author.
The purpose of this paper is to emphasize that the taking, assembling and averaging of the basic data for further use in an analysis of a reservoir requires a profound knowledge of many of the specialized disciplines of modern geology and petroleum engineering.
The various aspects of "Static Data," as presented in this paper, analyze that problem and specifically discuss the following major subheadings:
Porosity,
Permeability,
Facies Mapping,
Connate Water,
Relative Permeabilities and Capillary Pressures, and
Method of Least Squares.
This paper is essentially a general and philosophical discussion on the necessity for obtaining data quality and of the need for an integrated approach to be applied in a detailed analysis of any reservoir.
The correct taking, interpretation and usage of reservoir data are among the most important tasks of the petroleum engineer, and particularly of the reservoir engineer and geologist. On the quality, and to a much lesser degree on the quantity, of this information depends the success as well as the accuracy of all the subsequent geological and engineering studies and finally of the economic evaluations. Despite this paramount importance, very little is found on this subject either in petroleum literature or in university curricula. There are exceptions - e.g., the normal types of pressure build-up curves and the determination of the areal and volumetric average pressures, without explaining when to use which and why. At the present stage of knowledge of the science of reservoir physics, it appears that the analytical methods of solution (equations) are normally, from a mathematical and physical standpoint, much more exact than the basic data and particularly the "averages which are fed" into them. In layman's terms, the reservoir analyst often performs an exact multiplication of doubtfully reliable numbers. This lack of interest in the accuracy and representativeness of the basic data and in the methods of averaging them is usually explained by the simplicity of this problem, which can be solved by "common engineering sense;" this explanation is correct if it is backed by a thorough and uniform theoretical, as well as practical, understanding of this complex problem.
During the last fifteen years, many scientists, be they mathematicians, physicists, geologists, engineers, programmers, etc., advanced tremendously the understanding of reservoir mechanics and put it on firm theoretical, scientific foundations. Unfortunately, nearly nothing has been done in securing more representative data; most of the methods presently applied in obtaining, interpreting and averaging the basic data are still the same as those used when reservoir engineering was in its infancy and when an experienced reservoir analyst had only to compute the initial oil in place by volumetric methods.
In this paper, an attempt is made to show that the taking and assembling of some of the "GIVEN" is a real challenge and not a mundane task of obtaining some answer for any price. Great discretion and judgement has to be exercised in working with the basic data in order to obtain the most probable and physically logical answer to a specific reservoir problem. Because of its idiosyncratic nature, it is impossible to prepare a "universal cookbook" which satisfies all conditions: each reservoir and even each well presents a specific problem to be considered separately when planning, taking, interpreting and finally using the surface and subsurface data.
It is hoped that, by this "scratching of the surface," the industry, and particularly its technical personnel, will realize the magnitude and importance of proper and systematic data collecting, of their interpretation and of the averaging problems.
