CN114320284A - Method for evaluating stratum fracturing effect by using dipole acoustic wave time difference correlation matrix - Google Patents
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Abstract
The invention discloses a method for evaluating stratum fracturing effect by using a dipole acoustic time difference correlation matrix, which adopts the technical scheme that 1) dipole acoustic monopole waveform data MPB before fracturing and dipole acoustic monopole waveform data MPA after fracturing of a well to be explained are obtained, and the measurement unit is dB; 2) calculating a pre-fracturing monopole waveform time difference correlation matrix CMB and a post-fracturing monopole waveform time difference correlation matrix CMA by using dipole acoustic treatment software in the step 1); 3) calculating a difference matrix CMD of the time difference correlation matrix of the waveforms of the front and the rear monopoles before fracturing, wherein CMD is CMB-CMA; 4) and drawing a differential matrix imaging diagram of the time difference correlation matrix of the unipolar waveforms before and after the well fracturing to be explained.
Description
Technical Field
The invention belongs to the technical field of acoustic logging, and particularly relates to a method for evaluating a stratum fracturing effect by using a dipole acoustic time difference correlation matrix.
Background
The hydraulic fracturing technology is usually adopted for improving the productivity and the recovery ratio of an unconventional reservoir stratum, a micro seismic method, a well temperature logging method and a radioactive isotope tracing method are generally adopted for detecting the fracturing effect, but the defects of large error, complex process, radioactive pollution and the like exist, and the precise analysis and explanation of specific layer positions and depths are difficult due to the complex and changeable stratum conditions.
The method for detecting the fracturing effect by using the dipole acoustic wave mainly evaluates the distribution characteristics of the fractured cracks, the conventional method for evaluating the fractures by using the dipole acoustic wave mainly adopts a static analysis method including methods such as anisotropy, acoustic wave amplitude attenuation and the like, but the method cannot evaluate the dynamic change characteristics of the fractures before and after fracturing. CN110529087 discloses a method and a device for evaluating a hydraulic fracturing effect of a stratum, wherein the fracturing effect is determined by calculating the difference of energy envelopes of scattering waves before and after fracturing and the difference of slowness of elastic waves before and after fracturing at one depth point of a depth interval. The method has the limitation that the collected four-component data and the orientation of the instrument can only ensure that the device before and after fracturing is fixed and does not rotate under the laboratory condition, and the orientation of the instrument is random in the actual logging environment, so that the scattered wave energy envelopes obtained by the four components before and after fracturing cannot be directly subtracted theoretically. Assuming that the orientations of the instruments before and after fracturing are the same, inaccuracy still exists in the method, for example, when the normalized post-processing result g (z, t) calculated in the step 3 is w (z, t)/w0, and when the direct wave amplitude w0 is selected, the accuracy of the normalized post-processing result is difficult to guarantee due to individual difference among different processing personnel; when the difference Δ E between the elastic wave energy envelopes before and after fracturing at the depth z0 is calculated in the step 5, the direct wave amplitude w0 measured before and after fracturing may be different because dipole acoustic wave data before and after fracturing are obtained under different measurement environments at different times, and when w0 is selected twice before and after, the accuracy of Δ E is more difficult to guarantee due to individual differences of different processing personnel. Therefore, the method still has the problems of poor accuracy and poor reliability.
Disclosure of Invention
The invention aims to solve the technical problems and provides a method for evaluating the stratum fracturing effect by using a dipole acoustic wave time difference correlation matrix, which is simple, free from external interference, accurate, reliable and high in reliability.
The technical scheme comprises the following steps:
1) acquiring dipole acoustic monopole waveform data MPB before fracturing and dipole acoustic monopole waveform data MPA after fracturing of a well to be explained, wherein the measurement unit is dB;
2) the monopole wave form data MPB before fracturing and the monopole wave form data MPA after fracturing obtained in the step 1) are brought into dipole wave treatment software, and a monopole wave form time difference correlation matrix CMB before fracturing and a monopole wave form time difference correlation matrix CMA after fracturing are calculated;
3) calculating a difference matrix CMD of the time difference correlation matrix of the waveforms of the front and the rear monopoles before fracturing, wherein CMD is CMB-CMA;
4) and drawing a differential matrix imaging diagram of the time difference correlation matrix of the unipolar waveforms before and after the well fracturing to be explained.
In the step 2), the pre-fracturing monopole waveform time difference correlation matrix CMB and the post-fracturing monopole waveform time difference correlation matrix CMA of the well to be explained are both m multiplied by n order matrixes, wherein
in＝i1+nd1
jm＝j1+md2
In the formula: i.e. inFor data depth, the unit of measure is m;
d1the depth sampling interval is m;
n is 1,2, …, and the measurement unit is dimensionless;
jmfor data time difference, the measurement unit is mu s/ft;
d2the time difference sampling interval is set, and the measurement unit is mu s/ft;
m is 1,2, …, and the measurement unit is dimensionless.
In the step 3), the difference matrix CMD of the time difference correlation matrix of the monopole waveform before and after the well to be explained is an mxn order difference matrix,
after the imaging graph is obtained, the density degree of the color development part in the differential matrix imaging graph (difference matrix imaging graph for short) of the time difference correlation matrix of the unipolar waveforms before and after the well to be explained is observed through human eyes, so that the fracturing effect of the well section with the corresponding depth can be preliminarily judged, namely the higher the density degree is, the better the fracturing effect is.
Or the following grading evaluation can be further carried out:
5) dividing abnormal areas and well sections of corresponding depths in the differential matrix imaging graph based on the differential matrix imaging graph of the time difference correlation matrix of the unipolar waveforms before and after well fracturing to be explained;
6) and evaluating the fracturing effect according to the proportion of the color development part in the abnormal area in the total area of the abnormal area in the difference matrix imaging graph, wherein the larger the proportion of the area of the color development part is, the better the fracturing effect is.
In the step 5), the method for dividing the abnormal region includes: the method comprises the steps of taking a region which is continuously distributed along the well depth and has a similar area occupation ratio of color development parts in a difference matrix imaging graph as an abnormal region, dividing the difference matrix imaging graph into a plurality of abnormal regions according to the method, determining the top boundary depth HK1 and the bottom boundary depth HK2 of each abnormal region, respectively representing the top boundary depth and the bottom boundary depth of the Kth abnormal region, wherein the unit is m, K is a natural number, and finding out the well section with the depth corresponding to the abnormal region according to HK1 and HK 2.
In the step 6), the area ratio of the color developing part of the abnormal region is the ratio of the area of the color developing part to the total area of the corresponding abnormal region, and the calculation method is as follows: storing the difference matrix imaging graph of each abnormal region as a picture, and calculating the area ratio of the color development part of the abnormal region by using picture analysis software;
the fracturing effect is evaluated by calculating the area ratio of the color development part in the abnormal area, and the method specifically comprises the following steps:
the area of the color development part accounts for more than 10 percent, which shows that the fracturing effect is good,
the area of the color developing part is between 5 and 10 percent, which indicates that the fracturing effect is moderate,
the area ratio of the colored part is less than 5%, which indicates that the fracturing effect is poor.
In the method, the well pre-fracture dipole acoustic monopole waveform data MPB and the post-fracture dipole acoustic monopole waveform data MPA can be obtained by acquiring data through a dipole acoustic logging instrument; the dipole sonic processing software is a software for processing dipole sonic logging information, such as SoniView software of Gyo Geoerstone energy technology, Inc. of Beijing; the area ratio of the color part of the abnormal region can be calculated by picture analysis software, for example, Photoshop image processing software under the standard of Adobe corporation in the united states, the histogram function in the Photoshop image processing software can be used for counting the percentage of pixels with the color gradation range of 200-255 in the total pixels as the area ratio of the color part of the abnormal region. The above are merely examples, and those skilled in the art can select other suitable software to process data or images as required.
Has the advantages that:
the invention is a method for evaluating the fracturing effect by using the difference matrix of the time difference correlation matrix of the acoustic logging of the front dipole and the rear dipole before fracturing, the time difference correlation matrix used in the method is a parameter for describing the waveform similarity between different receivers, the size of the time difference correlation matrix is in the range of 0-1, the time difference correlation matrix is only related to the quality of the acquired data, normalization processing is not needed, the time difference correlation matrix is not influenced by the acquisition environment, the direction of an instrument and processing personnel, and the calculated data is more accurate and reliable; and drawing a differential matrix imaging graph by using the time difference correlation matrix of the front and rear unipolar waveforms of the well to be explained, and analyzing the proportion of the color areas in the abnormal areas corresponding to different well sections in the imaging graph so as to realize the evaluation of the fracturing effect. The method can continuously acquire data, dynamically evaluate the characteristics of the fracturing fracture aiming at specific layer positions and depths, is simple, visual and clear, can become a conventional technical means for fracturing detection, and provides powerful technical support for stable yield and yield increase in oil field development.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a graph of the P-well pre-fracture and post-fracture unipolar waveform time difference correlation matrix difference matrix imaging plotted in the example.
FIG. 3 is a graph showing the effect of the rating evaluation in the example.
FIG. 4 is a cross plot of the color area ratio of the difference matrix in the P-well difference matrix imaging graph and the sand adding amount in the fracturing construction.
Detailed Description
Referring to fig. 1, the method comprises the following specific steps:
1) acquiring dipole acoustic monopole waveform data (MPB) before fracturing and dipole acoustic monopole waveform data (MPA) after fracturing of a well to be explained, wherein the measurement unit is dB; the data can be acquired by a dipole sonic logging instrument, which is prior art and will not be described in detail.
2) Calculating a monopole waveform time difference Correlation Matrix (CMB) before fracturing and a monopole waveform time difference Correlation Matrix (CMA) after fracturing by using dipole sound wave processing software,
the pre-fracturing monopole waveform time difference correlation matrix CMB and the post-fracturing monopole waveform time difference correlation matrix CMA of the well to be explained are m multiplied by n order matrixes, wherein
in＝i1+nd1
jm＝j1+md2
In the formula: i.e. inFor data depth, the unit of measure is m;
d1the depth sampling interval is m;
n is 1,2, …, and the measurement unit is dimensionless;
jmfor data time difference, the measurement unit is mu s/ft;
d2the time difference sampling interval is set, and the measurement unit is mu s/ft;
m is 1,2, …, the measurement unit is dimensionless;
3) calculating a difference matrix CMD of the monopole waveform time difference correlation matrix before and after fracturing, wherein the difference matrix CMD of the monopole waveform time difference correlation matrix before and after fracturing of the well to be explained is an mxn order difference matrix,
4) drawing a differential matrix imaging diagram of the time difference correlation matrix of the unipolar waveforms before and after fracturing of the well to be explained: drawing the pre-fracturing unipolar waveform time difference correlation matrix and the post-fracturing unipolar waveform time difference correlation matrix as well as the difference matrix into an imaging graph by using drawing software;
after the imaging graph is obtained, the density degree of the color development part in the differential matrix imaging graph (difference matrix imaging graph for short) of the time difference correlation matrix of the unipolar waveforms before and after the well to be explained is observed through human eyes, so that the fracturing effect of the well section with the corresponding depth can be preliminarily judged, namely the higher the density degree is, the better the fracturing effect is.
5) Dividing abnormal regions of a differential matrix imaging map based on a differential matrix imaging map (a differential matrix imaging map for short) of a time difference correlation matrix of unipolar waveforms before and after well fracturing to be explained, determining the top boundary depth HK1 and the bottom boundary depth HK2 of the abnormal regions of an image (a color development part), confirming well sections with corresponding depths,
the HK1 and HK2 represent the top boundary depth and the bottom boundary depth of the Kth region respectively, and the unit is m;
6) evaluating the fracturing effect according to the proportion of the color development area of the imaging map of the abnormal region in the difference matrix imaging map:
the area of the color developing part is more than 10 percent, the fracturing effect is good,
the area of the color developing part is between 5 and 10 percent, the fracturing effect is moderate,
the area ratio of the color developing part is less than 5 percent, and the fracturing effect is poor.
Example (b):
referring to fig. 1, a Q field, using the invention, analyzes the fracturing effect of a P well.
1) Acquiring P well pre-fracturing dipole acoustic monopole waveform data (MPB1) and post-fracturing dipole acoustic monopole waveform data (MPA1), wherein the measurement unit is dB;
2) calculating a pre-fracturing unipolar waveform time difference correlation matrix (CMB1) and a post-fracturing unipolar waveform time difference correlation matrix (CMA1) by using SoniView software
Wherein i1＝1400.0m，in＝1500.0m，j1＝50μs/ft，jn＝150μs/ft
d1Is 0.1m, d2Is 2 mus/ft;
3) calculating a difference matrix CMD1 of the monopole waveform time difference correlation matrix before and after fracturing,
4) the difference matrix imaging graph of the time difference correlation matrix of the unipolar waveform before and after P well fracturing is drawn as shown in FIG. 2,
drawing the pre-fracturing unipolar waveform time difference correlation matrix and the post-fracturing unipolar waveform time difference correlation matrix as an imaging graph by using SoniView drawing software;
5) dividing abnormal regions of the difference matrix imaging graph into 3 sections based on a P well fracturing front monopole waveform time difference correlation matrix difference matrix imaging graph and a P well fracturing rear monopole waveform time difference correlation matrix difference matrix imaging graph, and respectively determining top boundary depth H11-1400 m, H21-1438 m, H31-1468 m, bottom boundary depth H12-1438 m, H22-1468 m and H32-1500 m of color rendering parts of the 3 sections of image abnormal regions; the well sections are 1400.0-1438.0m, 1438.0-1468.0m and 1468.0-1500.0m respectively;
6) respectively calculating the total area of the abnormal areas of the 3 sections in the difference matrix imaging graph and the area of the corresponding color development part, and converting to obtain the ratio of the area of the color development part in the area of the corresponding abnormal area;
taking a well section 1400.0-1438.0m as an example: through Photoshop image processing software, the percentage of the pixels in the color gradation range 200-255 in the well section difference matrix imaging graph in the total pixels is counted to be about 1% by utilizing the histogram function, namely the area percentage of the color development part of the abnormal region is about 1%.
Evaluating the fracturing effect of the P well according to the proportion of the area of the developing part of the imaging diagram of the abnormal area of the difference matrix imaging diagram:
the area of the color development part of the difference matrix in the 1400.0-1438.0m imaging graph of the well section accounts for about 1 percent, the fracturing effect is evaluated to be poor,
the area of the color development part of the difference matrix in an imaging graph of the well section 1438.0-1468.0m accounts for about 13 percent, the fracturing effect is evaluated to be good,
the area of the color development part of the difference matrix in an imaging graph of the well section 1468.0-1500.0m accounts for about 6.5 percent, and the fracturing effect is evaluated to be medium;
and (4) drawing an imaging graph according to the fracturing effect evaluation result by using SonicView software according to the figure 3, and submitting the fracturing effect evaluation result.
And (3) verification: generally, the higher the sand addition, the better the fracturing effect, so the sand addition data can be used to verify the reliability of the method. FIG. 4 is a cross-plot of the color area ratio of the difference matrix in the P-well difference matrix imaging plot and the sand addition amount in the fracturing construction, wherein the color area ratio of the P-well three-section difference matrix imaging plot and the sand addition amount are in a positive correlation relationship, namely the sand addition amount is higher when the color area ratio is larger, the fracturing effect is better, and the result is consistent with the result evaluated by the well.
Claims (6)
1. A method for evaluating the stratum fracturing effect by using a dipole acoustic wave time difference correlation matrix is characterized by comprising the following steps of:
1) acquiring dipole acoustic monopole waveform data MPB before fracturing and dipole acoustic monopole waveform data MPA after fracturing of a well to be explained, wherein the measurement unit is dB;
2) the monopole wave form data MPB before fracturing and the monopole wave form data MPA after fracturing obtained in the step 1) are brought into dipole wave treatment software, and a monopole wave form time difference correlation matrix CMB before fracturing and a monopole wave form time difference correlation matrix CMA after fracturing are calculated;
3) calculating a difference matrix CMD of the time difference correlation matrix of the waveforms of the front and the rear monopoles before fracturing, wherein CMD is CMB-CMA;
4) and drawing a differential matrix imaging diagram of the time difference correlation matrix of the unipolar waveforms before and after the well fracturing to be explained.
2. The method for evaluating the effectiveness of fracturing a formation using a dipole acoustic moveout correlation matrix of claim 1,
in the step 2), the pre-fracturing monopole waveform time difference correlation matrix CMB and the post-fracturing monopole waveform time difference correlation matrix CMA of the well to be explained are both m multiplied by n order matrixes, wherein
in＝i1+nd1
jm＝j1+md2
In the formula: i.e. inFor data depth, the unit of measure is m;
d1the depth sampling interval is m;
n is 1,2, …, and the measurement unit is dimensionless;
jmfor data time difference, the measurement unit is mu s/ft;
d2the time difference sampling interval is set, and the measurement unit is mu s/ft;
m is 1,2, …, and the measurement unit is dimensionless.
3. The method for evaluating the effectiveness of fracturing a formation using a dipole acoustic moveout correlation matrix of claim 1,
in the step 3), the difference matrix CMD of the time difference correlation matrix of the monopole waveform before and after the well to be explained is an mxn order difference matrix,
4. a method for evaluating the effectiveness of fracturing a formation using a dipole acoustic moveout correlation matrix as claimed in any of claims 1 to 3, further comprising the steps of:
5) dividing abnormal areas and well sections of corresponding depths in the differential matrix imaging graph based on the differential matrix imaging graph of the time difference correlation matrix of the unipolar waveforms before and after well fracturing to be explained;
6) and evaluating the fracturing effect according to the proportion of the color development part in the abnormal area in the total area of the abnormal area in the difference matrix imaging graph, wherein the larger the proportion of the area of the color development part is, the better the fracturing effect is.
5. The method for evaluating the effectiveness of fracturing a formation using a dipole acoustic moveout correlation matrix of claim 4,
in the step 5), the method for dividing the abnormal region includes: the method comprises the steps of taking a region which is continuously distributed along the well depth and has a similar area occupation ratio of color development parts in a difference matrix imaging graph as an abnormal region, dividing the difference matrix imaging graph into a plurality of abnormal regions according to the method, determining the top boundary depth HK1 and the bottom boundary depth HK2 of each abnormal region, respectively representing the top boundary depth and the bottom boundary depth of the Kth abnormal region, wherein the unit is m, K is a natural number, and finding out the well section with the depth corresponding to the abnormal region according to HK1 and HK 2.
6. The method for evaluating the effectiveness of fracturing a formation using a dipole acoustic moveout correlation matrix of claim 5,
in the step 6), the area ratio of the color developing part of the abnormal region is the ratio of the area of the color developing part to the total area of the corresponding abnormal region, and the calculation method is as follows: storing the difference matrix imaging graph of each abnormal region as a picture, and calculating the area ratio of the color development part of the abnormal region by using picture analysis software;
the fracturing effect is evaluated by calculating the area ratio of the color development part in the abnormal area, and the method specifically comprises the following steps:
the area of the color development part accounts for more than 10 percent, which shows that the fracturing effect is good,
the area of the color developing part is between 5 and 10 percent, which indicates that the fracturing effect is moderate,
the area ratio of the colored part is less than 5%, which indicates that the fracturing effect is poor.
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