Документ взят из кэша поисковой машины. Адрес
оригинального документа
: http://www.cplire.ru/Lab144/start/e_oil.html
Дата изменения: Mon Sep 24 15:02:27 2007 Дата индексирования: Mon Oct 1 23:24:04 2012 Кодировка: Поисковые слова: п п п п п п п п п п п п п п п п п п п п п п п п п п п |
In this chapter we will consider an example of visual expert system written on the Actor Prolog language. The expert system is intended for solving of the following problem. There are a lot of methods of oil field bed stimulation that increase output of the oil production: thermal, physical-chemical, gas, microbiological, and others. Selection of a method appropriated for given oil field is complex and very important stage of development of oil field. In the course of selection of the method one must account a lot of parameters like rock characteristics, reservoir characteristics, oil characteristics, reservoir water characteristics, native gas characteristics, bedded substances, mineral constituents, and others. A mistake in the selection of bed stimulation method can led to big expenses and material losses even before the beginning of the oil production because modern methods of bed stimulation require expensive reagents and apparatus. This expert system helps one to estimate the appropriateness of some known methods of bed stimulation on early stages of exploration of oil field, under the conditions of uncertainty and absence of some crucial information. The expert system implements the following principles of data analysis:
|
Fig. 1. Start of the expert system.
The Top-Most diagram consists of three blocks: the "Describe parameters of hydrocarbon field" block, the "Check adaptability of existed methods of oil production" block, and the "Display solution" block. |
Fig. 2. Selection of bed stimulation method.
Open the "Describe parameters of hydrocarbon field" window. The parameters of the oil field are grouped in separate blocks. |
Fig. 3. Describing of the parameters of hydrocarbon field.
Open blocks and enter the parameters of the oil field that you are know. If you do not know some parameters, left corresponding fields blank ones. |
Fig. 4. Input of the oil field parameters.
As you will define concretely the parameters of the oil field, the expert system will refine its exploration of the adaptability of the bed stimulation methods. The following bed stimulation methods are described in the expert system now: |
Fig. 5. A taxonomy of the oil field bed stimulation methods.
|
Fig. 6. Thermal methods.
|
Fig. 7. Physical-chemical methods.
|
Fig. 8. The first group of physical-chemical methods.
|
Fig. 9. The second group of physical-chemical methods.
|
Fig. 10. Gas methods.
|
Fig. 11. Nitrogen injection.
|
Fig. 12. Carbon dioxide injection.
|
Fig. 13. Microbiological methods.
|
Fig. 14. Biopolymer waterflooding.
The blocks of the diagrams that correspond to the appropriate bed stimulation methods are automatically colored green. If some doubts are cast upon the appropriateness of a method, corresponding block is marked by red color. At the same time the expert system outputs a list of appropriated bed stimulation methods to the "Display solution" text window. |
Fig. 15. A list of appropriated bed stimulation methods.
At the left mouse click the system outputs an explanation of its solution. |
Fig. 16. An explanation of elaborated decision.
In the course of the analysis of the oil field it is recommended to open several diagrams corresponding to the methods that are interesting for you at one time and order them by the "Window | Horizontal Tile" menu command. |
Fig. 17. Multiple-windows user interface.
After this one can observe upon the modification of the colors of corresponding diagram blocks in the course of modification of the oil field parameters. |
Fig. 18. Visualization of the decision making procedure.
This expert system is a commercial product and is not included into the standard package of Actor Prolog. Application of Actor Prolog makes it possible to use advantages of the object-oriented logic programming, namely:
|
Table of content |