Abstract: Methods and systems for determining a drilling-induced rock damage map are disclosed. The method includes obtaining a sonic dataset, including sonic waveforms recorded at a plurality of source-receiver separations for a plurality of source positions along an axis of a wellbore. The method further includes determining a log of a first metric using the sonic dataset and determining a map of a second metric using the sonic dataset. The method still further includes determining the drilling-induced rock damage map based, at least in part, on the log of the first metric and the map of the second metric.

Abstract: A method includes drilling a wellbore in a current well. An interval of the wellbore comprises a first portion of the wellbore and a second portion of the wellbore. The method also includes obtaining an offset drilling log and an offset lithology log for a geologically similar interval in an offset well and training a first machine learning model, using the offset drilling log, to produce a first trained machine learning model. The method further includes producing, using the first trained machine learning model, a forecasted drilling log for the second portion of the wellbore in the current well, training a second machine learning model, using a gradient boosting machine learning technique, the forecasted drilling log, and the offset lithology log, to produce a second trained machine learning model, and producing, using the second trained machine learning model, a forecasted lithology log for the second portion of the current well.

Abstract: A method for obtaining geological heterogeneity trends of a geological formation, including the steps: drilling wells (w1, w2, w3, w4, w5) that penetrate the formation, acquiring well logs (log 1, log 2) for each well (w1, w2, w3, w4, w5) as function of depth inter Vals (Dk) of the respective well, determining a third degree tensor (Tk, m, n), where a z-dimension denotes the depths, a x-dimension denotes the well logs, and a y-dimension denotes the wells, extracting matrices (L1k,m, L2k,m, . . . , LMk,n) from the tensor (Tk, m, n), clustering the matrices (L1k,n, L2k,n, . . . , LMk,n) based on the characteristics of the corresponding well logs (log 1, log 2) to a clustering result matrix, aggregating the clustering result matrix to a cluster ensemble (?1, ?2, . . . , ?M), and spatial partitioning the cluster ensemble (?1, ?2, . . . , ?M) to a map that shows the geological heterogeneity trends associated with cluster types of the wells (w1, w2, w3, w4, w5).

Abstract: A method including obtaining, by a computer processor, a sonic waveform for each of a plurality of source and receiver positions along a borehole, and a sonic wave propagation velocity of a target event for the plurality of positions. Further, performing, a linear moveout correction on the sonic waveforms based on the velocity and stacking the linear moveout corrected waveforms to generate a stacked waveform at the plurality of positions. The method further includes determining an arrival-time of the target event on the stacked waveforms based on an extremum of a first objective and predicting a candidate arrival-time of the target event for the sonic waveform at the plurality positions based on the arrival-time of the target event on the stacked waveforms, and the sonic velocity.

Abstract: Methods and systems for determining a drilling-induced rock damage map are disclosed. The method includes obtaining a sonic dataset, including sonic waveforms recorded at a plurality of source-receiver separations for a plurality of source positions along an axis of a wellbore. The method further includes determining a log of a first metric using the sonic dataset and determining a map of a second metric using the sonic dataset. The method still further includes determining the drilling-induced rock damage map based, at least in part, on the log of the first metric and the map of the second metric.

Abstract: A method including obtaining, by a computer processor, a sonic waveform for each of a plurality of source and receiver positions along a borehole, and a sonic wave propagation velocity of a target event for the plurality of positions. Further, performing, a linear moveout correction on the sonic waveforms based on the velocity and stacking the linear moveout corrected waveforms to generate a stacked waveform at the plurality of positions. The method further includes determining an arrival-time of the target event on the stacked waveforms based on an extremum of a first objective and predicting a candidate arrival-time of the target event for the sonic waveform at the plurality positions based on the arrival-time of the target event on the stacked waveforms, and the sonic velocity.