DAS same-well monitoring real-time microseismic effective event identification method based on deep learning
US-11899154-B2 · Feb 13, 2024 · US
US9798031B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9798031-B2 |
| Application number | US-201114111288-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 9, 2011 |
| Priority date | Aug 9, 2011 |
| Publication date | Oct 24, 2017 |
| Grant date | Oct 24, 2017 |
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A system and method for measuring a formation property in a wellbore is disclosed. In the method, an acoustic measurement tool is introduced into a wellbore. The acoustic measurement tool may include a transmitter and a plurality of sensors. At least one of the plurality of sensors may be positioned in a non-uniform spacing configuration. The transmitter may transmit energy into the formation. The plurality of sensors may measure energy received from the formation. Additionally, a time semblance of the formation may be determined using at least one time semblance algorithm generalized for non-uniform sensor spacing.
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What is claimed is: 1. A system for measuring a time semblance of a formation, comprising: a transmitter, wherein the transmitter transmits energy into the formation; a plurality of sensors comprising a plurality of consecutive sensors, wherein the plurality of sensors measures energy received from the formation, wherein at least one of the plurality of consecutive sensors is positioned in a non-uniform axial spacing configuration, and wherein the non-uniform axial spacing configuration of the at least one of the plurality of consecutive sensors is determined, at least in part, using a time semblance algorithm, wherein the time semblance algorithm comprises determining TS sum ( s j , t ) = ( ∑ i A ( s j , z i , t ) ) 2 ∑ i ( A ( s j , z i , t ) ) 2 × N , wherein t is a time, wherein N is a total number of the plurality of sensors, Ns is a total number of slowness values, i is a value from 1 to N, j is a value from 1 to Ns, z i denotes a position of sensor i along a tool, s j represents a slowness value of a waveform in the formation, and A(s j ,z i ,t) represents a progression of the waveform for a particular slowness s j ; and a data processing unit including at least one time semblance algorithm, wherein the data processing unit receives measurements from the plurality of sensors and processes the measurements to determine a time semblance of the formation. 2. The system of claim 1 , wherein the non-uniform spacing configuration comprises one of a spacing with one non-uniformly spaced sensor and a spacing determined using at least one non-linear mathematical expression. 3. The system of claim 1 , wherein the non-uniform spacing configuration comprises spacing optimized to reduce aliasing. 4. The system of claim 3 , wherein the time semblance algorithm is a min-max time semblance algorithm. 5. The system of claim 3 , wherein the time semblance algorithm is a sum time semblance algorithm. 6. The system of claim 3 , wherein the spacing optimized to reduce aliasing is determined using at least one iterative step. 7. The system of claim 1 , wherein the at least one time semblance algorithm includes a time semblance algorithm for non-uniform sensor spacing. 8. The system of claim 1 , wherein the at least one time semblance algorithm comprises one of either a sum time semblance algorithm or a min-max time semblance algorithm. 9. A method for measuring a time semblance of a formation, comprising: introducing an acoustic measurement tool into a wellbore, wherein the acoustic measurement tool includes a transmitter and a plurality of sensors comprising a plurality of consecutive sensors, wherein at least one of the plurality of consecutive sensors is positioned in a non-uniform axial spacing configuration, and wherein the non-uniform axial spacing configuration of the at least one of the plurality of consecutive sensors is determined, at least in part, using a time semblance algorithm, wherein the time semblance algorithm comprises determining TS sum ( s j , t ) = ( ∑ i A ( s j , z i , t ) ) 2 ∑ i
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