CN103399347B - 3D seismic data fast network visualization method - Google Patents
3D seismic data fast network visualization method Download PDFInfo
- Publication number
- CN103399347B CN103399347B CN201310369979.5A CN201310369979A CN103399347B CN 103399347 B CN103399347 B CN 103399347B CN 201310369979 A CN201310369979 A CN 201310369979A CN 103399347 B CN103399347 B CN 103399347B
- Authority
- CN
- China
- Prior art keywords
- seismic data
- plane
- row
- filesize
- survey line
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Geophysics And Detection Of Objects (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The invention provides a kind of 3D seismic data fast network visualization method, comprising: whole 3-d seismic data sets of the cell stores survey region of server; Server sets up the bitmap index of whole 3-d seismic data set; When the display survey region middle finger receiving client transmission determines the request message of local area image, server searches storage unit by bitmap index, obtain the specific three dimensional seismic data volume corresponding with plane characteristic point coordinate value, then locate in full picture based on specific three dimensional seismic data volume, obtain designated local region image; Server compresses designated local region image, obtains the topography after compressing; Server by compression after topography by Internet Transmission to client; Topography after client display compression.Improve from many aspects, thus improve the display speed of client display three-dimensional visualization image, improve Consumer's Experience.
Description
Technical field
The invention belongs to oil exploration technology field, be specifically related to a kind of 3D seismic data fast network visualization method.
Background technology
3-d seismic exploration has become the major technique of current oil-gas exploration and development.Collect a large amount of 3-d seismic data sets by 3-d seismic exploration technology, then 3-d seismic data set is stored in memory device.At present, usually adopt 3D seismic data visualization method, be convenient for people to carry out Geologic modeling and geological research thereof to 3D seismic data.
3D seismic data network visualization refers to: server end stores a large amount of 3-d seismic data sets; When a certain client needs the geological data visual image reading a certain survey region, server end searches memory device, reads required 3-d seismic data set; Again the 3-d seismic data set read is visualized as image, then by this image by Internet Transmission to each client, show this image at client display interface.
3-d seismic data set represents with coordinate (X, Y, Z) usually, and wherein, X and Y represents planimetric coordinates, and Z represents underground longitudinal degree.3-d seismic data set has and takies the large feature of storage space, such as: the acquisition plane of 400 square kilometres, if get a sampling point every 20 meters, then this plane needs to get (1000 × 1000) individual sampling point, each sampling point longitudinally down equidistantly gets 8000 sampling points (longitudinal 8000 down the got sampling points of certain sampling point are called a seismic trace plane) again, then final total sample is (1000 × 1000 × 8000), if the amplitude 4byte record of each sampling point, so, the storage space that takies of 3-d seismic data set is about 30G.
In prior art, usually all 3-d seismic data sets corresponding for acquisition plane are divided into several data segments, each data segment are stored in corresponding son file, and then each son file is stored on disk.Search a large amount of 3-d seismic data sets that disk stores for convenience, the mode at Database index file can be adopted.
But the database index inquiry velocity of routine is very slow, the usual seek rate of data volume of 30G is more than 1 second, and index file itself needs the space taking about 1 G, thus cause the 3-d seismic data set of server end to certain acquisition plane to become figure speed slow, and then reduce the speed of three-dimensional visualization image transmitting to client, have impact on the experience of user.
Summary of the invention
For the defect that prior art exists, the invention provides a kind of 3D seismic data fast network visualization method, improve from many aspects, thus improve the display speed of client display three-dimensional visualization image, improve Consumer's Experience.
The technical solution used in the present invention is as follows:
The invention provides a kind of 3D seismic data fast network visualization method, comprise the following steps:
S1, whole 3-d seismic data sets of the cell stores survey region of server;
S2, described server sets up the bitmap index of described whole 3-d seismic data set;
S3, when the described survey region middle finger of display receiving client transmission determines the request message of local area image, wherein, described request message carries the plane characteristic point coordinate value of described designated local region;
Described server searches described storage unit by described bitmap index, obtain the specific three dimensional seismic data volume corresponding with described plane characteristic point coordinate value, then locate in described full picture based on described specific three dimensional seismic data volume, obtain described designated local region image;
S4, described server compresses described designated local region image, obtains the topography after compressing;
S5, the topography after described compression is given described client by Internet Transmission by described server;
S6, described client shows the topography after described compression.
Preferably, in S1, whole 3-d seismic data sets of described cell stores survey region are specially:
By the horizontally disposed sequentially survey line of n bar, { survey line 1, survey line 2... survey line n} form described survey region; If the plane sampling number that each bar survey line is arranged respectively is { the plane number of samples n} of the plane number of samples 1 of survey line 1, the plane number of samples 2... survey line n of survey line 2, each plane sampled point belongs to a seismic trace, and the number of samples that the seismic trace of each plane sampled point comprises is constant P; Therefore, the 3-d seismic data set corresponding to each bar survey line takies storage size and is respectively M={M
1, M
2... M
n; Wherein, the plane number of samples i*4 byte * P of Mi=survey line i;
S1.1, makes Ziwen piece number number=1;
Constant is set to Q;
Make i=1;
S1.2, judges M
iwhether be more than or equal to Q, if judged result is yes, then perform S1.3; If judged result is no, then perform S1.4;
S1.3, by M
iwhole 3-d seismic data sets of place survey line press X from small to large sequentially stored in the n-th umber son file; Then make number=number+1, i=i+1, circulation performs S1.2-S1.4, until by 3-d seismic data set corresponding for all surveys line all stored in son file; Wherein, X represents the coordinate of 3-d seismic data set in x-axis direction;
S1.4, reads M
i, M
i+1... M
i+j; Wherein, j meets following two constraint conditions:
Constraint condition 1:M
i+ M
i+1...+M
i+jbe more than or equal to Q;
Constraint condition 2:j is minimum value;
Will by X from small to large sequentially successively by M
i, M
i+1... M
i+jwhole 3-d seismic data sets of place survey line are stored in the n-th umber son file; Then make number=number+1, i=i+j+1, circulation performs S1.2-S1.4, until by 3-d seismic data set corresponding for all surveys line all stored in son file.
Preferably, S2, the bitmap index that described server is set up is specially:
By plane sampling point distributions situation, described survey region grid is turned to f row, the grid that n is capable, described grid is made up of n*f net point, wherein, f is the { maximal value in the plane number of samples n} of the plane number of samples 1 of survey line 1, the plane number of samples 2... survey line n of survey line 2; N is the survey line sum that survey region comprises;
If net region, net point place exists plane sampled point, then this net point fills " 1 "; Otherwise if net region, net point place does not exist plane sampled point, then this net point fills " 0 ".
Preferably, in S3, described server searches described storage unit by described bitmap index, obtains the specific three dimensional seismic data volume corresponding with described plane characteristic point coordinate value and is specially:
If need the plane characteristic point coordinate value of searching to be (a, b);
Described bitmap index is from below to up: { the 1st row, the 2nd row ... n-th line };
Read the 1st row the 1st column of figure, the 1st row the 2nd column of figure in order ... the 1st row n-th column of figure, the 2nd row the 1st column of figure, the 2nd row the 2nd column of figure ... the 2nd row n-th column of figure ... until when reading the capable b column of figure of a, stop numeral and read; In the reading process of above-mentioned numeral, perform the following step:
S31, if Ziwen piece number number=1, constant is set to Q, filesize=0, line number i=1;
S32, with behavior circulating unit, by sequentially reading every a line successively from top to bottom;
By the numeral of the from left to right each grid filling of order reading i-th row, if the numeral read is " 1 ", then make filesize=filesize+4 byte * P; If the numeral read is " 0 ", then filesize does not change;
After having read the i-th row, judge whether filesize is more than or equal to Q, if judged result is yes, then performed S33; If judged result is no, then perform S34;
S33, makes number=number+1, and i=i+1, filesize return 0, returns S32;
S34, continues the numeral of reading i-th+1 row, the numeral of the i-th+2 row ... the numeral that the i-th+j is capable, in the process reading numeral, if the numeral read is " 1 ", then makes filesize=filesize+4 byte * P; If the numeral read is " 0 ", then filesize does not change; Wherein, j meets following two constraint conditions:
Constraint condition 1:filesize is more than or equal to Q;
Constraint condition 2:j is minimum value;
Make number=number+1, i=i+j+1, filesize make zero, and return S32;
Circulation performs S32 to S34, until read the capable b column of figure of a, exports current number value, meanwhile, exports current filesize.
Preferably, S4, described server compresses described designated local region image, obtains the topography after compressing and is specially:
S4.1, sorts the probability that all pigments of described designated local region image occur according to it;
S4.2, selects maximum more than one color of probability of occurrence as reservation look;
S4.3, by the residue color of described designated local region image with retain look and carry out color-match, obtain respectively and remain color respectively corresponding most match;
S4.4, replaces with corresponding with it most match, obtains the topography after compressing by described residue color.
Preferably, in S4.3, carry out color-match and be specially: set and retain chromatic number amount as H; Ask respectively each residue color and each retain the aberration root mean square of look, the minimum reservation look of gained root mean square is the most match of this residue color.
Preferably, in S5, the topography after described compression is given described client by Internet Transmission by described server employing tile flow graph sheet transmission technology.
Preferably, the topography after described compression is given described client by Internet Transmission by described server employing tile flow graph sheet transmission technology, is specially:
S51, the topography after described compression is divided into several grids by described server, obtains grid image;
S52, described server reads the image display area of described client, in described grid image, then locate the boundary fitting image mated with described image display area size;
S53, described boundary fitting image is preferably transferred to described client by described server; Then, remaining grid image is progressively transferred to described client by described server.
Beneficial effect of the present invention is as follows:
3D seismic data fast network visualization method provided by the invention, has the following advantages:
(1) bitmap index array is placed in internal memory and carries out loop-around data and search, on the one hand, the storage space that bitmap index takies is little, on the other hand, efficiency data query is high, the 3-D data volume bitmap index of 30G only takies 122KB (1000*1000/8), and seek rate reaches 0.01 second.
(2) transmit after needing the image of transmission to carry out compression of images, image effective compressibility on the basis of high-fidelity is 10 times again, thus reduces network bandwidth burden, improves transmission speed.
(3) adopt tile stream picture transmission technology, improve transmission speed more than 20 times, thus improve 3-D seismics mass data body in client end response speed.
Accompanying drawing explanation
Fig. 1 is 3D seismic data fast network visualization method schematic flow sheet provided by the invention;
Fig. 2 is a kind of survey region sampling point distributions schematic diagram provided by the invention;
Fig. 3 is the sample area schematic diagram of irregularity;
Fig. 4 is the bitmap index obtained after Fig. 3 polishing.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in detail:
As shown in Figure 1, the invention provides a kind of 3D seismic data fast network visualization method, comprise the following steps:
S1, whole 3-d seismic data sets of the cell stores survey region of server;
S2, described server sets up the bitmap index of described whole 3-d seismic data set;
S3, when the described survey region middle finger of display receiving client transmission determines the request message of local area image, wherein, described request message carries the plane characteristic point coordinate value of described designated local region;
Described server searches described storage unit by described bitmap index, obtain the specific three dimensional seismic data volume corresponding with described plane characteristic point coordinate value, then locate in described full picture based on described specific three dimensional seismic data volume, obtain described designated local region image;
S4, described server compresses described designated local region image, obtains the topography after compressing;
S5, the topography after described compression is given described client by Internet Transmission by described server;
S6, described client shows the topography after described compression.
The present invention is optimized above steps, improves the display speed of client display three-dimensional visualization image comprehensively, realizes details below describe in detail to above-mentioned steps:
(1) data storage section
In the present invention, whole 3-d seismic data sets of the cell stores survey region of server, the mode of server stores data is directly related with bitmap index, only have when server adopts following manner to store data, could realize subsequently through the object of bitmap index fast finding to desired data.
Concrete, by the horizontally disposed sequentially survey line of n bar, { survey line 1, survey line 2... survey line n} form survey region; If the plane sampling number that each bar survey line is arranged respectively is { the plane number of samples n} of the plane number of samples 1 of survey line 1, the plane number of samples 2... survey line n of survey line 2, each plane sampled point belongs to a seismic trace, and the number of samples that the seismic trace of each plane sampled point comprises is constant P; Therefore, the 3-d seismic data set corresponding to each bar survey line takies storage size and is respectively M={M
1, M
2... M
n; Wherein, the plane number of samples i*4 byte * P of Mi=survey line i;
For convenience of description, enumerate an example simplified, as shown in Figure 2, survey region is made up of 5 surveys line; Wherein, the plane sampling number of survey line 1 is 3, that is: the network of filling " 1 " in survey line 1 is counted, and the plane sampling number of survey line 2 is 5, and the plane sampling number of survey line 3 is 5, and the plane sampling number of survey line 4 is 2, and the plane sampling number of survey line 5 is 2.For each plane sampled point, it longitudinally also comprises P=800 longitudinal sampled point, and namely these 800 longitudinal sampled points form a seismic trace.Suppose that the byte of a storage sampled point is 4 bytes, then, in survey line 1, all data need the storage space M taken
1=3*4 byte * 800 ≈ 9.3KB, by identical calculating, calculates: M
2≈ 15.6KB; M
3≈ 15.6KB; M
4≈ 6.3KB; M
5≈ 6.3KB.
S1.1, makes Ziwen piece number number=1;
Constant is set to Q;
Make i=1;
S1.2, judges M
iwhether be more than or equal to Q, if judged result is yes, then perform S1.3; If judged result is no, then perform S1.4;
S1.3, by M
iwhole 3-d seismic data sets of place survey line press X from small to large sequentially stored in the n-th umber son file; Then make number=number+1, i=i+1, circulation performs S1.2-S1.4, until by 3-d seismic data set corresponding for all surveys line all stored in son file; Wherein, X represents the coordinate of 3-d seismic data set in x-axis direction;
S1.4, reads M
i, M
i+1... M
i+j; Wherein, j meets following two constraint conditions:
Constraint condition 1:M
i+ M
i+1...+M
i+jbe more than or equal to Q;
Constraint condition 2:j is minimum value;
Will by X from small to large sequentially successively by M
i, M
i+1... M
i+jwhole 3-d seismic data sets of place survey line are stored in the n-th umber son file; Then make number=number+1, i=i+j+1, circulation performs S1.2-S1.4, until by 3-d seismic data set corresponding for all surveys line all stored in son file.
In practical application, the sampling number corresponding due to each survey line is numerous, the substantial amounts of the 3-d seismic data set stored, and therefore, Q is set to 400M usually.But for convenience of description, still for Fig. 2, suppose Q=15KB; Then, the data space M of survey line 1 correspondence is first judged
1whether be greater than 15KB, due in Fig. 2, M
1for 9.3KB, do not reach 15KB, then to lastrow circulation, judge M
1+ M
2whether be greater than 15KB, for Fig. 2, due to M
1+ M
2be greater than 15KB, then by the son file of all data of survey line 1 and survey line 2 correspondence stored in number=1; Then continue, to lastrow circulation, to judge M
3whether be greater than 15KB, for Fig. 2, due to M
3≈ 15.6KB > 15KB, then by the son file of all data of survey line 3 correspondence stored in number=2; The rest may be inferred, by the son file of all data of survey line 4 and survey line 5 correspondence stored in number=3.By this kind of data storage method, on the one hand, consider that then son file quantity is too much, and access efficiency can be caused to reduce if a corresponding son file of survey line; Therefore, in the present invention, if the data volume of certain survey line does not reach setting, then this survey line and a upper survey line being merged is stored in a son file, the data volume stored in each son file that final guarantee obtains all reaches setting, while guarantee data sectional stores, also avoid son file quantity too much.In above process, the data space that survey line is corresponding can be called the cumulative length of this survey line.
In addition, for a son file, e.g., the son file of number=1, the data in this son file are by X-axis sequential storage from small to large.Such as: survey line 1 plane sampled point is from left to right set to plane sampled point a, plane sampled point b, plane sampled point c.Suppose seismic trace P=4, then storage mode is: a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, c4.If data take 4 bytes, then the position of c2 in son file 1 is: 10*4 byte=40 byte.
(2) data query part is carried out by bitmap index
Server searches described storage unit by described bitmap index, obtains the specific three dimensional seismic data volume corresponding with described plane characteristic point coordinate value and is specially:
Set up bitmap index, the data volume polishing in irregular sampling region is become regular rectangle.Such as, a sample area is the data volume of Fig. 3, and polishing becomes the bitmap index shown in Fig. 4.Two-dimensional array is set up with maximum x value and maximum y value, the virtual part filled is recorded as 0 in two-dimensional array afterwards, the part having data volume to exist is recorded as 1 in two-dimensional array, each data record has only come with 1 bite, therefore, the data volume of an about 30G only needs the array of indexes setting up a 122KB (1000 × 1000/8), thus has greatly saved storage space.
Data query process is:
If need the plane characteristic point coordinate value of searching to be (a, b);
Described bitmap index is from below to up: { the 1st row, the 2nd row ... n-th line };
Read the 1st row the 1st column of figure, the 1st row the 2nd column of figure in order ... the 1st row n-th column of figure, the 2nd row the 1st column of figure, the 2nd row the 2nd column of figure ... the 2nd row n-th column of figure ... until when reading the capable b column of figure of a, stop numeral and read; In the reading process of above-mentioned numeral, perform the following step:
S31, if Ziwen piece number number=1, constant is set to Q, filesize=0, line number i=1;
S32, with behavior circulating unit, by sequentially reading every a line successively from top to bottom;
By the numeral of the from left to right each grid filling of order reading i-th row, if the numeral read is " 1 ", then make filesize=filesize+4 byte * P; If the numeral read is " 0 ", then filesize does not change;
After having read the i-th row, judge whether filesize is more than or equal to Q, if judged result is yes, then performed S33; If judged result is no, then perform S34;
S33, makes number=number+1, and i=i+1, filesize return 0, returns S32;
S34, continues the numeral of reading i-th+1 row, the numeral of the i-th+2 row ... the numeral that the i-th+j is capable, in the process reading numeral, if the numeral read is " 1 ", then makes filesize=filesize+4 byte * P; If the numeral read is " 0 ", then filesize does not change; Wherein, j meets following two constraint conditions:
Constraint condition 1:filesize is more than or equal to Q;
Constraint condition 2:j is minimum value;
Make number=number+1, i=i+j+1, filesize make zero, and return S32;
Circulation performs S32 to S34, until read the capable b column of figure of a, exports current number value, meanwhile, exports current filesize.
Still for Fig. 2, suppose the data needing reading the 4th row the 2nd row sampled point, then set up the bitmap index of Fig. 2.If number=1, filesize=0, Q=15KB;
First, read the cumulative length of the 1st row, filesize is 9.3KB, does not reach 15KB, then to lastrow circulation, read the cumulative length of the 1st row and the 2nd row, filesize is 24.9KB, now, filesize, more than 15KB, makes number=2, and filesize makes zero;
Then, to lastrow circulation, read the cumulative length of the 3rd row, filesize is 15.6KB > 15KB, then make number=3, and filesize makes zero;
Then, to lastrow circulation, now, be recycled to the 4th row, therefore, number=3 is the Ziwen piece number needing the data place of reading; Read the 4th row the 1st column data, calculating the filesize of the 4th row the 1st column data, is 4 byte * 800=3.1KB, therefore, knows and needs the data read in the 3.1KB position of the 3rd son file.So, directly in data storage cell, find the 3rd son file, and navigate to the 3.1KB position of the 3rd son file, namely can read the data that required sampled point is corresponding.
Method of being searched data by bitmap index provided by the invention, bitmap index array can be placed in internal memory carries out loop-around data and searches, in internal memory, carry out circulation searching search fast a lot than the index file of setting up in a database generally used, on the one hand, the storage space that bitmap index takies is little, on the other hand, efficiency data query is high.
(3) compression of images part
S4.1, sorts the probability that all pigments of described designated local region image occur according to it;
S4.2, selects maximum more than one color of probability of occurrence as reservation look;
S4.3, by the residue color of described designated local region image with retain look and carry out color-match, obtain respectively and remain color respectively corresponding most match;
Carry out color-match to be specially: set and retain chromatic number amount as H; Ask respectively each residue color and each retain the aberration root mean square of look, the minimum reservation look of gained root mean square is the most match of this residue color.
S4.4, replaces with corresponding with it most match, obtains the topography after compressing by described residue color.
(4) image stage
Topography after described compression is given described client by Internet Transmission by server employing tile flow graph sheet transmission technology.
Concrete, comprise the following steps:
S51, the topography after described compression is divided into several grids by described server, obtains grid image;
S52, described server reads the image display area of described client, in described grid image, then locate the boundary fitting image mated with described image display area size;
S53, described boundary fitting image is preferably transferred to described client by described server; Then, remaining grid image is progressively transferred to described client by described server.
In prior art, the disposable transmission of client's required image, thus take a large amount of bandwidth, the client end response time is long; And in the present invention, by tile stream picture transmission technology, 3-D seismics mass data body is shown fast in client, shorten the response time.
In sum, 3D seismic data fast network visualization method provided by the invention, improves from following three aspects, and has the following advantages:
(1) bitmap index array is placed in internal memory and carries out loop-around data and search, on the one hand, bitmap index efficiency data query is high, and the storage space taken is little, in the present invention, the 3-D data volume bitmap index of 30G only takies 122KB (1000*1000/8), and seek rate reaches 0.01 second.
(2) transmit after needing the image of transmission to carry out compression of images, image effective compressibility on the basis of high-fidelity is 10 times again, thus reduces network bandwidth burden, improves transmission speed.
(3) adopt tile stream picture transmission technology, improve transmission speed more than 20 times, thus improve 3-D seismics mass data body in client end response speed.
The technology of above-mentioned three aspects of integrated application, 3D seismic data fast network visualization method provided by the invention is applied in the test of actual seismic data of 2000 square kilometres, reach the response speed of 0.7 second, comparatively conventional method is fast more than at least 10 times, therefore, the response speed of the mass seismic data body Real time displaying that the present invention reaches, more can meet the requirement of industry and production.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should look protection scope of the present invention.
Claims (7)
1. a 3D seismic data fast network visualization method, is characterized in that, comprises the following steps:
S1, whole 3-d seismic data sets of the cell stores survey region of server;
S2, described server sets up the bitmap index of described whole 3-d seismic data set;
S3, when the described survey region middle finger of display receiving client transmission determines the request message of local area image, wherein, described request message carries the plane characteristic point coordinate value of described designated local region;
Described server searches described storage unit by described bitmap index, obtain the specific three dimensional seismic data volume corresponding with described plane characteristic point coordinate value, then locate in full picture based on described specific three dimensional seismic data volume, obtain described designated local region image;
S4, described server compresses described designated local region image, obtains the topography after compressing;
S5, the topography after described compression is given described client by Internet Transmission by described server;
S6, described client shows the topography after described compression;
Wherein, in S1, whole 3-d seismic data sets of described cell stores survey region are specially:
Described survey region is by horizontally disposed sequentially survey line { survey line 1, the survey line 2 of n bar ... survey line n} forms; If the plane sampling number that each bar survey line is arranged respectively is { the plane number of samples 1 of survey line 1, the plane number of samples 2 of survey line 2 ... the plane number of samples n} of survey line n, each plane sampled point belongs to a seismic trace, and the number of samples that the seismic trace of each plane sampled point comprises is constant P; Therefore, the 3-d seismic data set corresponding to each bar survey line takies storage size and is respectively M={M
1, M
2m
n; Wherein, the plane number of samples i*4 byte * P of Mi=survey line i;
S1.1, makes Ziwen piece number number=1;
Constant is set to Q;
Make i=1;
S1.2, judges M
iwhether be more than or equal to Q, if judged result is yes, then perform S1.3; If judged result is no, then perform S1.4;
S1.3, by M
iwhole 3-d seismic data sets of place survey line press X from small to large sequentially stored in the n-th umber son file; Then make number=number+1, i=i+1, circulation performs S1.2-S1.4, until by 3-d seismic data set corresponding for all surveys line all stored in son file; Wherein, X represents the coordinate of 3-d seismic data set in x-axis direction;
S1.4, reads M
i, M
i+1m
i+j; Wherein, j meets following two constraint conditions:
Constraint condition 1:M
i+ M
i+1+ M
i+jbe more than or equal to Q;
Constraint condition 2:j is minimum value;
Will by X from small to large sequentially successively by M
i, M
i+1m
i+jwhole 3-d seismic data sets of place survey line are stored in the n-th umber son file; Then make number=number+1, i=i+j+1, circulation performs S1.2-S1.4, until by 3-d seismic data set corresponding for all surveys line all stored in son file.
2. 3D seismic data fast network visualization method according to claim 1, it is characterized in that, S2, the bitmap index that described server is set up is specially:
By plane sampling point distributions situation, described survey region graticule mesh is turned to the capable grid of f row n, described grid is made up of n*f net point, and wherein, f is { the plane number of samples 1 of survey line 1, the plane number of samples 2 of survey line 2 ... maximal value in the plane number of samples n} of survey line n; N is the survey line sum that survey region comprises;
If net region, net point place exists plane sampled point, then this net point fills " 1 "; Otherwise if net region, net point place does not exist plane sampled point, then this net point fills " 0 ".
3. 3D seismic data fast network visualization method according to claim 2, it is characterized in that, in S3, described server searches described storage unit by described bitmap index, obtains the specific three dimensional seismic data volume corresponding with described plane characteristic point coordinate value and is specially:
If need the plane characteristic point coordinate value of searching to be (a, b);
Described bitmap index is from below to up: { the 1st row, the 2nd row ... n-th line };
Read the 1st row the 1st column of figure, the 1st row the 2nd column of figure in order ... 1st row n-th column of figure, the 2nd row the 1st column of figure, the 2nd row the 2nd column of figure ... 2nd row n-th column of figure ... until when reading the capable b column of figure of a, stop numeral and read; In the reading process of above-mentioned numeral, perform the following step:
S31, if Ziwen piece number number=1, constant is set to Q, filesize=0, line number i=1;
S32, with behavior circulating unit, by sequentially reading every a line successively from top to bottom;
By the numeral of the from left to right each grid filling of order reading i-th row, if the numeral read is " 1 ", then make filesize=filesize+4 byte * P; If the numeral read is " 0 ", then filesize does not change;
After having read the i-th row, judge whether filesize is more than or equal to Q, if judged result is yes, then performed S33; If judged result is no, then perform S34;
S33, makes number=number+1, and i=i+1, filesize return 0, returns S32;
S34, continues the numeral of reading i-th+1 row, the numeral of the i-th+2 row ... the numeral that i-th+j is capable, in the process reading numeral, if the numeral read is " 1 ", then makes filesize=filesize+4 byte * P; If the numeral read is " 0 ", then filesize does not change; Wherein, j meets following two constraint conditions:
Constraint condition 1:filesize is more than or equal to Q;
Constraint condition 2:j is minimum value;
Make number=number+1, i=i+j+1, filesize make zero, and return S32;
Circulation performs S32 to S34, until read the capable b column of figure of a, exports current number value, meanwhile, exports current filesize.
4. 3D seismic data fast network visualization method according to claim 1, is characterized in that, S4, and described server compresses described designated local region image, obtains the topography after compressing and is specially:
S4.1, sorts the probability that all colours of described designated local region image occurs according to it;
S4.2, selects maximum more than one color of probability of occurrence as reservation look;
S4.3, by the residue color of described designated local region image with retain look and carry out color-match, obtain respectively and remain color respectively corresponding most match;
S4.4, replaces with corresponding with it most match, obtains the topography after compressing by described residue color.
5. 3D seismic data fast network visualization method according to claim 4, is characterized in that, in S4.3, carries out color-match and is specially: set and retain chromatic number amount as H; Ask respectively each residue color and each retain the aberration root mean square of look, the minimum reservation look of gained root mean square is the most match of this residue color.
6. 3D seismic data fast network visualization method according to claim 1, is characterized in that, in S5, the topography after described compression is given described client by Internet Transmission by described server employing tile flow graph sheet transmission technology.
7. 3D seismic data fast network visualization method according to claim 6, is characterized in that, the topography after described compression is given described client by Internet Transmission by described server employing tile flow graph sheet transmission technology, is specially:
S51, the topography after described compression is divided into several grids by described server, obtains grid image;
S52, described server reads the image display area of described client, in described grid image, then locate the boundary fitting image mated with described image display area size;
S53, described boundary fitting image prioritised transmission is given described client by described server; Then, remaining grid image is progressively transferred to described client by described server.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310369979.5A CN103399347B (en) | 2013-08-22 | 2013-08-22 | 3D seismic data fast network visualization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310369979.5A CN103399347B (en) | 2013-08-22 | 2013-08-22 | 3D seismic data fast network visualization method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103399347A CN103399347A (en) | 2013-11-20 |
| CN103399347B true CN103399347B (en) | 2016-01-27 |
Family
ID=49563002
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310369979.5A Active CN103399347B (en) | 2013-08-22 | 2013-08-22 | 3D seismic data fast network visualization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103399347B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870396B (en) * | 2014-03-10 | 2017-02-01 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Earthquake data cache method |
| CN104133243B (en) * | 2014-08-05 | 2017-02-15 | 吉林大学 | Seismic data visualization method and device |
| CN107197217B (en) * | 2017-04-19 | 2020-08-14 | 西安空间无线电技术研究所 | Satellite high-frame-frequency image data real-time slicing transmission method |
| CN111767264A (en) * | 2019-04-02 | 2020-10-13 | 中国石油化工股份有限公司 | Distributed storage method and data reading method based on geological information coding |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0531515B1 (en) * | 1991-03-27 | 1995-08-23 | Exxon Production Research Company | Displaying n dimensional seismic data in an n-1 dimensional format |
| US7289500B1 (en) * | 2003-07-17 | 2007-10-30 | Novell, Inc. | Method and system for reliable multicast data transmission |
| CN101778100A (en) * | 2009-12-31 | 2010-07-14 | 深圳市蓝韵实业有限公司 | Method for realizing communication between three-dimensional image server and client |
| CN101917449A (en) * | 2010-09-01 | 2010-12-15 | 中国地质大学（武汉） | Three-dimensional spatial data transmission-oriented application layer communication method |
| CN101944132A (en) * | 2010-09-30 | 2011-01-12 | 武汉大学 | Tile map data organization method |
| CN101493528B (en) * | 2009-03-13 | 2011-09-14 | 中国海洋石油总公司 | Magnanimity earthquake three-dimensional visualized display method |
-
2013
- 2013-08-22 CN CN201310369979.5A patent/CN103399347B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0531515B1 (en) * | 1991-03-27 | 1995-08-23 | Exxon Production Research Company | Displaying n dimensional seismic data in an n-1 dimensional format |
| US7289500B1 (en) * | 2003-07-17 | 2007-10-30 | Novell, Inc. | Method and system for reliable multicast data transmission |
| CN101493528B (en) * | 2009-03-13 | 2011-09-14 | 中国海洋石油总公司 | Magnanimity earthquake three-dimensional visualized display method |
| CN101778100A (en) * | 2009-12-31 | 2010-07-14 | 深圳市蓝韵实业有限公司 | Method for realizing communication between three-dimensional image server and client |
| CN101917449A (en) * | 2010-09-01 | 2010-12-15 | 中国地质大学（武汉） | Three-dimensional spatial data transmission-oriented application layer communication method |
| CN101944132A (en) * | 2010-09-30 | 2011-01-12 | 武汉大学 | Tile map data organization method |
Non-Patent Citations (3)
| Title |
|---|
| 刘丽娟.三维地震数据的可视化.《中国新通信》.2010,(第7期),第55-57页. * |
| 戴晨光 等.一种用于实时可视化的海量地形数据组织与管理方法.《系统仿真学报》.2005,第17卷(第2期),第406-409/413页. * |
| 马仁安 等.可视化技术及在三维地震解释中的应用.《计算机工程》.2003,第29卷(第5期),第139-141页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103399347A (en) | 2013-11-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103399347B (en) | 3D seismic data fast network visualization method | |
| CN102721977B (en) | High-precision converted wave anisotropy stacking velocity analysis method | |
| CN106779417A (en) | The collection of engineering investigation information digitalization, management and integrated application method | |
| US20140058713A1 (en) | Seismic modeling system and method | |
| CN104166163B (en) | Tomography curved surface extraction method based on three-dimensional big data quantity seismic data cube | |
| US10663609B2 (en) | Combining multiple geophysical attributes using extended quantization | |
| CN106682377B (en) | A kind of the EO-1 hyperion extraction and quantitative estimation method of drilling core altered mineral | |
| CN104391906A (en) | Method for dynamic browsing of vehicle-mounted mass point cloud data | |
| CN103969683B (en) | Method for picking position faces in batched mode based on constraint in three-dimensional seismic interpretation | |
| CN103955558A (en) | Method for collecting and processing engineering investigation data of different industries | |
| CN101493528A (en) | Magnanimity earthquake three-dimensional visual display method | |
| CN106355031A (en) | Data value degree calculation method based on analytic hierarchy process | |
| CN110672072A (en) | Information multivariate interpretation and characterization method for fractured rock mass structure | |
| CN103377303A (en) | Curve surface measurement system and method | |
| CN110827406A (en) | Method for realizing rapid three-dimensional reconstruction of large water network tunnel | |
| CN109298450A (en) | Earthquake-capturing observation system property analysis method and device | |
| CN112700531A (en) | Building tilt model layered household display method fused with vector household diagram | |
| CN104317536A (en) | Device and method for storing seismic data cube and reading seismic channels | |
| CN109189725A (en) | The obj file lossless compression method of rule-oriented building | |
| CN104156242A (en) | Cache data preloading and loading method and device | |
| CN106777117A (en) | A kind of automatic identifying method of horizontal stratum tectonic landform | |
| CN106504319B (en) | Reservoir Three Dimensional Contrast map generalization method and device between well | |
| CN109918371A (en) | A kind of methods, devices and systems of storage, the access of seismic interpretation performance data | |
| CN111966732B (en) | Full-intelligent geological mapping method, device, equipment and readable storage medium | |
| CN108761533B (en) | A kind of method, apparatus and system of determining P-S wave velocity ratio |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |