US 12,013,510 B2
Multi-resolution based method for automated acoustic log depth tracking
Ting Lei, Arlington, MA (US)
Assigned to Schlumberger Technology Corporation, Sugar Land, TX (US)
Appl. No. 17/759,050
Filed by Schlumberger Technology Corporation, Sugar Land, TX (US)
PCT Filed Jan. 20, 2021, PCT No. PCT/US2021/014152
§ 371(c)(1), (2) Date Jul. 19, 2022,
PCT Pub. No. WO2021/150585, PCT Pub. Date Jul. 29, 2021.
Claims priority of provisional application 62/963,310, filed on Jan. 20, 2020.
Prior Publication US 2023/0037176 A1, Feb. 2, 2023
Int. Cl. G01V 1/50 (2006.01)
CPC G01V 1/50 (2013.01) [G01V 2200/16 (2013.01); G01V 2210/42 (2013.01); G01V 2210/47 (2013.01); G01V 2210/6222 (2013.01)] 11 Claims
OG exemplary drawing
 
1. A method of characterizing properties of structures of interest in a formation traversed by a borehole, comprising:
operating a sonic logging tool in the borehole to transmit acoustic signals that probe nearby formation structures and to receive acoustic signals that result from interaction with the nearby formation structures;
generating waveform data associated with the received acoustic signals as a function of measured depth in the borehole;
acquiring and/or processing the waveform data to identify or label clusters of Slowness-Time-Coherence peaks;
tracking at least one cluster of Slowness-Time-Coherence peaks over varying depth values;
performing a coherence optimization process on the at least one cluster of Slowness-Time-Coherence peaks to produce data;
generating a log of an acoustic property of the formation as a function of depth based on the data produced by the coherence optimization process;
using an optimization process to determine the acoustic property; and
applying a tracking algorithm to cluster vertices of different resolution Slowness-Time-Coherence peaks,
wherein the optimization process is a multi-resolution based coherence optimization process which includes grouping the different resolution Slowness-Time-Coherence peaks, and
wherein a machine-learning based algorithm is used to perform the grouping of the different resolution Slowness-Time-Coherence peaks.