GB2212636A - Identifying data format - Google Patents
Identifying data format Download PDFInfo
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- GB2212636A GB2212636A GB8826207A GB8826207A GB2212636A GB 2212636 A GB2212636 A GB 2212636A GB 8826207 A GB8826207 A GB 8826207A GB 8826207 A GB8826207 A GB 8826207A GB 2212636 A GB2212636 A GB 2212636A
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- data
- format
- program
- representation
- record
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/31—Programming languages or programming paradigms
- G06F8/313—Logic programming, e.g. PROLOG programming language
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
A method is disclosed of identifying, from a list of known data formats, a particular format for a set of data. A representation of at least a portion of the data is created and from the representation, characteristics of the data are obtained. Utilizing predetermined logic rules, the data characteristics are matched to known data characteristics of each known data format until a match is accomplished. Thereafter, an indication is generated of the data format that has been matched.
Description
"METHOD FOR DETERMINING T: VORKaT OF SEISMIC
TRACE DATA"
The present invention relates to a method for identifying the format of seismic trace data anc, more particularly, to such a method which uses internal logic rules, such as provided by artificial intelligence, to identify the format.
The successful processing of data is highly dependent upon the particular format in which the data has been recorded. For example, companies that process seismic traces acquire the data from many different service companies, each of which records the data in their own particular format(s). In order for the processing to be successfully accomplished, the data needs to be placed into a format that is compatible with the particular computer programs that are to be used to process the data, for example programs to increase the signal-to-noise ratio. Various data recording standards have been published by organizations; however, these standards have not been widely adhered to so seismic data processing includes the need for an initial determination of the format of the data that has been received from an outside source.
Most companies that process data have developed or acquired a suite of data processing programs that process the data in the many different formats, i.e., a single processing program for each format or set of related formats. Again, the problem is to select the appropriate processing program for the particular format, as well as the determination of certain peculiar processing parameters that are to be used in the procession.
Therefore, there is a need for a simple method of deter- mining the format of the data.
The present invention has been contemplated to overcome the forgoing deficiencies and to meet the above described need. The present invention provides a method of identifying, from a list of known data formats, a par titular format for a set of data. In the method, a repre sensation is created of at least a portIon of the data, and from that representation, characteristics of the data are obtaIned. Utilizing predetermined logic rules, supplied by experienced users and translated into a form used by an expert system shell, the data characteristIcs are matched to known data characteristics for each known data format until a match is accomplished. Expert system shells are programs written for programmable digital ccmputers that manipulate symbols in predefined ways.In particular, they allow the backward chaining of the detailed description. Thereafter, a report is generated indicating that the data is in a particular matched data format. By using this program, a set of data can be easily and quickly reviewed and an indication of the par titular data format is provided, as well as any particular additional known parameters that are required in the processing of the data.
The present invention provides a method of iden- tifying, from a list of known data formats, a particular format for a set of data by using a programmable digital computer. While this method can be utilized for any data format, for the purpose of this discussion, the fIeld of use will be identified as processing seismic data used in the exploratIon for oil and gas. Basically, once a seismic tape containing data is acquired from an outside source, it is first loaded on a computer system and a representation of the content of the data is created.
This representation is a uniform formatted representation, i.e., a formatted hexidecimal dump of the data. An example of a representation is shown in Table I.
The representation is electronically transmitted to the computer where programs of the present invention reside. When the user invokes the program, the name of the file containing the representation must be supplied to the program and other particular information (described herein below) about the file that might be available may be supplied. With the available information, the program then scans the first portion of the representation to Identify the location and value of particular data items to obtain characteristics of the data. Then, the program identifies the particular data format, the name of the particular processing program useful in processing data in that format and the values of any parameters that might be needed during such processing.
Specifically, before the program of the present invention can be run, it is necessary to transform the data set into a uniformally formatted representation. Tho first portion, for example 480 bytes, of each physical record of the tape are generated in hexadecimai form.
Each record is then represented by a line that contains the number of bytes in the physical record and the number of the physical record, followed by 12 lines containing the hexadecimal representation of the data. The hexadecimal representation is arranged in groups of four nibbles separated by a single space.
Once this has been transferred to the machIne where the program runs, the following information is asked of the user:
1. The name of the file containing the Input data.
2. Whether observers notes are available
for this data, and if yes:
(a) the number of traces per seismic
record.
(b) the number of auxiliary traces per
seismic record.
(c) the sample interval used for
recording the data.
(d) the length of the trace data in
seconds.
3. Whether a hardcopy of the representa
tion is available to user and if so the format used
to record the trace data.
4. Whether the data was initially recorded
in analog or digital form.
The representation of the data is then analyzed to obtain data characteristics, for example, the program will scan the data representation at particular locations and retrieve the values at such locations. These characteristics are thereafter used in the matching process with logic rules. The logic rules utilized in the present invention are a set of knowledge relationships captured from experienced people and written using the Personal
Consultant Plus#, a computer program marketed by Texas
Instruments CorporatIon. The program accomplishes its determination by the application of the set of rules that have been determined to solve this problem correctly about 80-85% of the time. Each of the rules is an indepenoent piece of information that is known to experienced people who can make a parameter determination. The Personal Consultant Plus# determines the manner and order by which these rules are used in any particular run of the program.
Some of the logical rules can be classified as facts about the problem of program parameter determination. Some of the rules can be classified as generally disseminated practices about the problem of recognizing seismic formats. A third classification of rules is that one developed after long discussions with experienced people who are familiar with the program and parameter determination and truly reflects their expertise in per forming these tasks. Table II shows examples of these roles.
One of the strengths of this program is that there can be any number of rules that have been accumulated and coded into the system, thereby permitting a high degree of confidence in the outputted format determination.
The predetermined logic rules developed are applied against the characteristics of the data by a logic process called backward chaining. In other words, a first or trial data format is chosen from the list of known data formats and set as a goal. For such data to be in the first data format, one or several rules must be activated, i.e., have all of their premises be proved true. The required rules are found and their premises are examinec.
If the facts needed to determine the truth of the premises are not known, then these facts are set as subgoals, and the cycle of selecting rules occurs again. If a sufficient set of rules is able to activate, there is a match for the rules, then the data is in the first data format.
However, If the rules do not activate, then a new trial data format is selected as a goal, the respective logic rules are found, and the backward chaining of rules and facts is applied as before. The program will continue with each known data format until a match is found. If no match is found, then the program will indicate that no match was found.
When the program has determined to the predetermined satisfaction limit the particular format of the data, an indication or display is provided to the user of the name of the preferred processing program and any associated processing variables, needed to process the data.
Six examples of the indication are provided in Table III.
Wherein the present invention has been described in particular relation to the examples included herein, it should be understood that other and further modIfications, apart from those shown or suggested herein, may be made within the scope and spirit of the present invention. TABLE I
BYTES READ 3200 RECORD 1
1 C3D3 C9C5 D5E3 40C1 D4D6 C3D6 40C1 D9C5 C140 E3F3 C161 F540 D3C9 D5C5 40F1 F7F5 4040 4040 4040 4040
41 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040
81 C4C5 D4E4 E740 E2C5 C740 4040 40F1 F7F5 E240 C6D6 D940 E2D7 7DE2 40F1 6160 F2F7 F0F0 4040 4040 4040 121 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 161 C4C5 D5E2 C9E3 E840 F6F2 F5F0 F7F9 F4F8 C340 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 201 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 241 C5D5 C440 C5C2 C3C4 C9C3 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040 4040
BYTES READ 400 RECORD 2
1 0000 0000 0000 00AF 0000 1F0C 0010 0006 07D0 07D0 0FA0 0000 0001 0078 0001 0001 0000 0000 0000 0000
41 0000 0000 0000 0000 0001 0000 0000 0002 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000
81 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 121 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 161 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 201 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 241 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000
BYTES READ 16240 RECORD 3
1 0000 96F1 0000 0001 0000 01BA 0000 0001 0000 0000 0000 01BA 0000 0001 0001 0000 0000 0001 0000 0001
41 0000 002B 0000 0000 0000 0051 FFFF FFAF 0000 0000 0000 0000 0000 0000 0001 0001 0005 2080 0001 A130
81 0000 0000 0000 0000 0001 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0FA0 07D0 0000 121 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 161 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 201 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 241 BF19 C580 BE4A 2800 3EFA 6800 3F12 3300 3F10 9B00 3EEF 8800 3E99 B000 BE35 6000 BF15 A480 BF22 CE00
BYTES READ 16240 RECORD 4
1 0000 96F2 0000 0002 0000 01BA 0000 0002 0000 0000 0000 01BA 0000 0002 0001 0000 0000 0001 0000 0001
41 0000 001E 0000 0000 0000 0051 FFFF FFAF 0000 0000 0000 0000 0000 0000 0001 0001 0005 2080 0001 A130
81 0000 0000 0000 0000 0001 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0FA0 07D0 0000 121 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 161 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 201 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 241 BF35 8400 BF37 4000 BF30 6E00 BF2C 5E00 BF2D AE00 BF2C 3800 BF22 9600 BF1A 8800 BEF2 5800 BEA8 2800 TABLE II Rule069 STD-RULES/antecedent If 1) the sample interval used to record the data in micro
seconds is known, and
2) the measure of certainty associated with the sample
interval used to record the data in microseconds,
Then, it is definite (100%) that the sample interval used to record the data in milliseconds is the sample interval used to record the data in microseconds divided by 1000.
IF: SI IS KNOWN AND CERTAINTY SI
THEN: SI-MILLI = VALUE SI / 1000
PREMISE: ($AND (RENOWN FRAME SI)
(MEASURE1 FRAME SI))
ACTION: (DO-ALL
(CONCLUDE FRAME SI-MILLI
(FQUOTIENT (VAL1 FRAM SI) 1000) TALLY 100))
ANTECEDENT: YES Rule074 STD-RULES
If 1) both 1*4 and R*4 are equally likely, and
2) the measure of certainty associated with the format of
the recorded data,
Then there is weakly suggestive evidence (20%) that the format of the recorded data is R*4.
IF: SEL-DFMT (VAL FRAME DFMT) AND CERTAINTY DFMT
THEN: DFMT = R*4 CF 20
PREMISE: ($AND (SEL-DFMT
(VAL FRAME DFMT))
(MEASURE1 FRAME DFMT))
ACTION: (DO-ALL
(CONCLUDE FRAME DFMT R*4 TALLY 20))
Rule072 STD-RULES
If the number of line headers is 0,
Then, 1) there is strongly suggestive evidence (80%) that the
first 32 words of the binary header is all zeros,
and
2) there is strongly suggestive evidence (80%) that the
tape is a variant of the SEG-Y format.
IF: NO-LH-1 = 0
THEN: VALUE-BH = GET-O-BH CF 80 AND A-SEGY CF 80
PREMISE: ($AND (SAME FRAME NO-LH-1 0))
ACTION: (DO-ALL
(CONCLUDE FRAME VALUE-SH
(GET-0-BH) TALLY 80)
(CONCLUDE FRAME A-SEGY YES TALLY 80))
TABLE I T T Example 1. The system found that there were only seven seconds of data in the file even though the user had indicated that there were eight.
MPS-STD-1 CONCLUSIONS:
A major recommendation is as follows: Use the program EXCH to reformat the file, fully accounting for all of the subsidiary recommendations. (74%)
The complete list of parameters for the selected program is as follows:
Sample interval 2 97%
Number of regular traces 16 87%
Number of auxiliary traces 0 87%
Number of samples per trace 3500 74%
Length of the trace header 240 74%
Number of line headers 2 90%
Data format R*4 100%
Record number position bytes 11 and 12 100%
Trace number position bytes 15 and 16 100%
A subsidiary recommendation is as follows: It appears that the recording has been shortened to 7 seconds. (80%)
Example 2. The system notes that the record numbers are large at the beginning of the file and might exceed the pro gram capability by the time the end of the fiie is reached.
MPS-STD-1 CONCLUSIONS:
A major recommendation is as follows: Use the program EXCY to reformat the file, fully accounting for all of the subside iary recommendations. (83%)
The complete list of parameters for the selected program is as follows:
Sample interval 2 97%
Number of regular traces 48 88%
Number of auxiliary traces 0 99%
Number of samples per trace 3500 83%
Length of the trace header 240 83%
Number of line headers 2 90%
Data format R*4 100%
Record number position bytes 11 and i2 100% Trace number position bytes 15 and 16 100%
A subsidiary recommendation is as follows: The data contains record numbers that are greater than loo,000. The file can be reformatted, but the records should be renumbered (7283 Example 3.The system notes that there is an additional tenth of a second of data in the file.
MPS-STD-1 CONCLUSIONS:
A major recommendation is as follows: Use the program EXC.E to reformat the file, fully accounting for all of the subsidiary recommendations. (40%)
The complete list of parameters for the selected program is as follows:
Sample interval 4 95%
Number of regular traces 24 40%
Number of auxiliary traces 0 53%
Number of samples per trace 1175 65%
Length of the trace header 240 65 Number of line headers 2 90%
Data format R*4 100%
Record number position bytes 221 and 222 80%
Trace number position bytes 223 and 224 80%
A subsidiary recommendation is as follows: It appears that there are actually 4.7 seconds of data, rather than the 4.6 seconds indicated in the observer notes. This file appears to be in CDP sort sequence. (72%)
Example 4.For the case of a SEGD formatted file, additional parameters are not required to process the file.
M-STD-1 CONCLUSIONS:
A major recommendation is as follows: The program SEGD should be used to reformat the file because it is in SEG-D format.
Example 5. ere two problems were found. The record numbers were not recorded and the traces have been shortened.
MPS-STD-1 CONCLUSIONS:
A major recommendation is as follows: Use the program EXCE to reformat the file, fully accounting for all of the subsidiary recommendations. (43%)
The complete list of parameters for the selected program is as follows:
Sample interval 2 97%
Number of regular traces 48 54%
Number of auxiliary traces 0 86%
Number of samples per trace 1000 94%
Length of the trace header 240 94%
Number of line headers 2 90%
Data format R*4 100%
Record number position unknown 43%
Trace number position bytes 15 and 16 54%
A subsidiary recommendation is as follows: It appears that the recording has been shortened to 2 seconds. (80%) There are no record numbers in the trace headers. The file can be processed, but the record numbers will need to be generated by renumbering. (43%)
Example 6.There may be a problem with the interpretatIon of this case because the user didn't dump enough of the seismic data file as input to the program.
MPS-STD-1 CONCLUSIONS:
A major recommendation is as follows: Use the program EXCH to reformat the file, fully accounting for all of the subsidiary recommendations. (43%)
The complete list of parameters for the selected program is as follows:
Sample interval 2 97%
Number of regular traces 18 54%
Number of auxiliary traces 0 86%
Number of samples per trace 3000 92%
Length of the trace header 240 92%
Number of line headers 2 90%
Data format R*4 93%
Record number position unknown 43t Trace number position bytes 15 and 16 54%
A subsidiary recommendation is as follows: The number of traces MAY be limited by the number of records that have been dumped, you ought to dump more records and re-run this consultation. Both the binary header and the observer notes indicate that there are 48 traces.
Claims (7)
1. A method of identifying, from a list of known data formats, the particular format for a set of data, comprising:
(a) creating a representation of at least a
portion of the data;
(b) from the representation, obtaining
characteristics of the data;
(c) utilizing predetermined logic rules,
matching the data characteristics of (b) to known
data characteristics for the known data formats until
a match is accomplished; and
(d) generating an indication that the data
is in the matched data format.
2. The method of Claim 1 wherein the representation of the data is uniformly formatted.
3. The method of Claim 2 wherein the unIformly formatted data is in hexidecimal form.
4. The method of Claim 1 wherein step (b) comprises analyzing a first portion of the data to identify the location and value of particular data items.
5. The method of Claim 1 wherein before step (c), including the step of inputting user-known data crar- acteristics.
6. The method of Claim 1 wherein step (d) includes utilizing known data processing requirements for each known data format, generating an indication of preferred processing variables.
7. The method of Claim 1 wherein the set of data are seismic data traces.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US12150087A | 1987-11-17 | 1987-11-17 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| GB8826207D0 GB8826207D0 (en) | 1988-12-14 |
| GB2212636A true GB2212636A (en) | 1989-07-26 |
Family
ID=22397117
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| GB8826207A Withdrawn GB2212636A (en) | 1987-11-17 | 1988-11-09 | Identifying data format |
Country Status (1)
| Country | Link |
|---|---|
| GB (1) | GB2212636A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1324216A1 (en) * | 2001-12-28 | 2003-07-02 | Deutsche Thomson-Brandt Gmbh | Machine for classification of metadata |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112241426A (en) * | 2019-07-16 | 2021-01-19 | 中国石油天然气集团有限公司 | Seismic data conversion method and device based on dynamic track head |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0062777A2 (en) * | 1981-04-09 | 1982-10-20 | Recognition Equipment Incorporated | OCR and bar code reader using area array |
| EP0144202A2 (en) * | 1983-11-25 | 1985-06-12 | Sumitomo Electric Industries Limited | Optical reader |
| EP0157354A2 (en) * | 1984-03-28 | 1985-10-09 | Hitachi, Ltd. | Method for designating a recognition mode in a hand-written character/graphic recognizer |
| EP0217655A2 (en) * | 1985-09-27 | 1987-04-08 | Kabushiki Kaisha Toshiba | Method for reading a document and a document reading apparatus utilizing an image buffer |
| GB2182796A (en) * | 1985-09-27 | 1987-05-20 | Sony Corp | Character recognition system |
-
1988
- 1988-11-09 GB GB8826207A patent/GB2212636A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0062777A2 (en) * | 1981-04-09 | 1982-10-20 | Recognition Equipment Incorporated | OCR and bar code reader using area array |
| EP0144202A2 (en) * | 1983-11-25 | 1985-06-12 | Sumitomo Electric Industries Limited | Optical reader |
| EP0157354A2 (en) * | 1984-03-28 | 1985-10-09 | Hitachi, Ltd. | Method for designating a recognition mode in a hand-written character/graphic recognizer |
| EP0217655A2 (en) * | 1985-09-27 | 1987-04-08 | Kabushiki Kaisha Toshiba | Method for reading a document and a document reading apparatus utilizing an image buffer |
| GB2182796A (en) * | 1985-09-27 | 1987-05-20 | Sony Corp | Character recognition system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1324216A1 (en) * | 2001-12-28 | 2003-07-02 | Deutsche Thomson-Brandt Gmbh | Machine for classification of metadata |
| WO2003056454A1 (en) * | 2001-12-28 | 2003-07-10 | Thomson Licensing S.A. | Method and apparatus for automatic detection of data types for data type dependent processing |
| US7359917B2 (en) | 2001-12-28 | 2008-04-15 | Thomson Licensing Llc | Method and apparatus for automatic detection of data types for data type dependent processing |
| KR100934537B1 (en) | 2001-12-28 | 2009-12-29 | 톰슨 라이센싱 | Method and apparatus for automatically detecting data type for data type dependent processing |
Also Published As
| Publication number | Publication date |
|---|---|
| GB8826207D0 (en) | 1988-12-14 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| WAP | Application withdrawn, taken to be withdrawn or refused ** after publication under section 16(1) |