METHOD AND SYSTEM FOR DIRECT SLOWNESS DETERMINATION OF DISPERSIVE WAVES IN A WELLBORE ENVIRONMENT
A system and method for effective estimation of properties of a formation using acoustic array processing is disclosed. An acoustic tool is directed to a zone of interest in the formation and generates a first signal. Real data corresponding to the first signal is then received. One or more basic parameters are provided as input. The basic parameters may include parameters relating to the acoustic tool or parameters relating to the zone of interest. A time semblance shear slowness and a frequency semblance shear slowness are determined using the basic parameters. A mask is then selected using the determined time semblance and frequency semblance shear slowness values and used to isolate a dispersion curve. A shear slowness value is selected from the dispersion curve and quality control is performed on the selected shear slowness value.
1 . A method for fracture identification and characterization, comprising:
positioning a magnetic dipole transmitter and a magnetic dipole receiver within a borehole in a subterranean formation, at least one of the magnetic dipole transmitter and the magnetic dipole receiver being tilted with respect to an axis of the borehole;
generating a time-varying electromagnetic (EM) signal with the magnetic dipole transmitter;
measuring a response of the formation to the time-varying EM signal using the magnetic dipole receiver, the response comprising at least two depths of the formation and at least two azimuthal orientations of the formation with respect to the axis of the borehole;
generating a first image of the formation based, at least in part, on the response; and
determining at least one fracture characteristic based, at least on part, on the first image and a synthetic fracture image.
2 . The method of claim 1 , wherein generating the first image of the formation based, at least in part, on the response and the synthetic fracture image comprises generating the first image of the formation using at least one of
phase values from the response;
amplitude values from the response;
attenuation values from the response; and
resistivity values calculated using at least one of the phase values, amplitude values, and attenuation values from the response.
3 . The method of claim 1 , wherein determining at least one fracture characteristic based, at least on part, on the first image and the synthetic fracture image comprises
constructing the synthetic fracture image using model fracture characteristics;
comparing the synthetic fracture image to a feature in the first image; and
adjusting the model fracture characteristics until the synthetic fracture image matches the feature within a threshold.
4 . The method of claim 1 , wherein determining at least one fracture characteristic based, at least on part, on the first image and the synthetic fracture image comprises
determining a set of potential model fracture characteristics combinations;
for each combination of potential model fracture characteristics,
generating a synthetic fracture image from the combination of potential model fracture characteristics;
correlating a first feature of the synthetic fracture image with a second feature in the first image; and
determining a correlation value; and
determining the potential model fracture characteristic with the highest correlation value among all combinations of potential model fracture characteristics.
5 . The method of claim 4 , wherein correlating the first feature of the synthetic fracture image with the second feature in the first image comprises
determining a type of the second feature;
identifying an azimuthal shift between the first feature and the second feature;
identifying a depth shift between the first feature and the second feature; and
shifting one of the first image and the synthetic fracture image so that the first feature and the second feature are aligned in azimuth and depth.
6 . The method of claim 5 , wherein determining the correlation value comprises calculating the correlation of image values between the shifted one of the first image and the synthetic fracture image and other one of the first image and the synthetic fracture image.
7 . The method of claim 5 , wherein determining the type of the second feature comprises determining if the feature comprises one of
a first set of resistivity values that are higher than the resistivity values at adjacent depths in the formation; and
a second set of resistivity values that are lower than the resistivity values at adjacent depths in the formation.
8 . The method of claim 1 , wherein determining at least one fracture characteristic based, at least on part, on the first image and the synthetic fracture image comprises determining at least one of a presence, shape, size, average resistivity value, and edge location of the fracture.
9 . The method of claim 1 , wherein both the magnetic dipole transmitter and the magnetic dipole receiver are tilted with respect to the axis of the borehole.
10 . The method of claim 1 , wherein the magnetic dipole transmitter and the magnetic dipole receiver are co-located with respect to the axis of the borehole.
11 . A system for fracture identification and characterization, comprising:
a magnetic dipole transmitter coupled to a tool body;
a magnetic dipole receiver coupled to the tool body, at least one of the magnetic dipole transmitter and the magnetic dipole receiver being tiled with respect to an axis of the tool body;
an information handling system communicably coupled to the magnetic dipole transmitter and the magnetic dipole receiver, the information handling system comprising a processor and a memory device coupled to the processor, the memory device containing a set of instruction that, when executed by the processor, cause the processor to:
generate a time-varying electromagnetic (EM) signal with the magnetic dipole transmitter;
measure a response of the formation to the time-varying EM signal using the magnetic dipole receiver, the response comprising at least two depths of a formation and at least two azimuthal orientations of the formation with respect to the axis of the tool body;
generate a first image of the formation based, at least in part, on the response; and
determine at least one fracture characteristic based, at least on part, on the first image and a synthetic fracture image.
12 . The system of claim 11 , wherein the set of instructions that causes the processor to generate the first image of the formation based, at least in part, on the response and the synthetic fracture image further causes the processor to generate the first image of the formation using at least one of
phase values from the response;
amplitude values from the response;
attenuation values from the response; and
resistivity values calculated using at least one of the phase values, amplitude values, and attenuation values from the response.
13 . The system of claim 11 , wherein the set of instructions that causes the processor to determine at least one fracture characteristic based, at least on part, on the first image and the synthetic fracture image further causes the processor to
construct the synthetic fracture image using model fracture characteristics;
compare the synthetic fracture image to an feature in the first image; and
adjust the model fracture characteristics until the synthetic fracture image matches the feature within a threshold.
14 . The system of claim 11 , wherein the set of instructions that causes the processor to determine at least one fracture characteristic based, at least on part, on the first image and the synthetic fracture image further causes the processor to
determine a set of potential model fracture characteristics combinations;
for each combination of potential model fracture characteristics,
generate a synthetic fracture image from the combination of potential model fracture characteristics;
correlate a first feature of the synthetic fracture image with a second feature in the first image; and
determine a correlation value; and
determine the potential model fracture characteristic with the highest correlation value among all combinations of potential model fracture characteristics.
15 . The system of claim 14 , wherein the set of instructions that causes the processor to correlate the first feature of the synthetic fracture image with the second feature in the first image further causes the processor to
determine a type of the second feature;
identify an azimuthal shift between the first feature and the second feature;
identify a depth shift between the first feature and the second feature; and
shift one of the first image and the synthetic fracture image so that the first feature and the second feature are aligned in azimuth and depth.
16 . The system of claim 15 , wherein the set of instructions that causes the processor to determine the correlation value further causes the processor to calculate the correlation of image values between the shifted one of the first image and the synthetic fracture image and other one of the first image and the synthetic fracture image.
17 . The system of claim 15 , wherein the set of instructions that causes the processor to determine the type of the second feature further causes the processor to determine if the second feature comprises one of
a first set of resistivity values that are higher than the resistivity values at adjacent depths in the formation; and
a second set of resistivity values that are lower than the resistivity values at adjacent depths in the formation.
18 . The system of claim 11 , wherein the fracture characteristic comprises at least one of a presence, shape, size, average resistivity value, and edge location of the fracture.
19 . The system of claim 11 , wherein both the magnetic dipole transmitter and the magnetic dipole receiver are tilted with respect to the axis of the tool body.
20 . The system of claim 11 , wherein the magnetic dipole transmitter and the magnetic dipole receiver are co-located on the tool body.