A method may include obtaining various well logs or various core samples regarding a geological region of interest. The method may further include determining various permeability values, various porosity values, and various dolomite volume fraction values regarding the geological region of interest using the well logs or the core samples. The dolomite volume fraction values may correspond to a percentage of dolomite in a total mineral volume. The method may further include determining, using the porosity values, various permeability thresholds corresponding to various predetermined reservoir qualities. The method may further include generating, using the permeability thresholds, the permeability values, and the dolomite volume fraction values, a reservoir model including various dolomite boundaries defining the predetermined reservoir qualities. The method may further include determining a hydrocarbon trap prediction using the reservoir model.

A method for seismic processing includes extracting, using a first machine learning model, one or more seismic features from seismic data representing a subsurface domain, receiving one or more well logs representing one or more subsurface properties in the subsurface domain, and predicting, using a second machine learning model, the one or more subsurface properties in the subsurface domain at a location that does not correspond to an existing well based on the seismic data, the one or more well logs, and the one or more seismic features that were extracted from the seismic data.

A method for seismic processing includes extracting, using a first machine learning model, one or more seismic features from seismic data representing a subsurface domain, receiving one or more well logs representing one or more subsurface properties in the subsurface domain, and predicting, using a second machine learning model, the one or more subsurface properties in the subsurface domain at a location that does not correspond to an existing well based on the seismic data, the one or more well logs, and the one or more seismic features that were extracted from the seismic data.

Systems and methods of controlling drilling operations including Sliding With Indexing For Toolface (SWIFT) and Variable Weight Drilling (VWD) techniques. The methods and systems may include systems and devices for controlling the drilling operations, including systems and devices capable of automatically determining drilling parameters and setting operating parameters for drilling in a wellbore. The systems and methods may also determine a change in weight on bit and/or toolface, determine a timeframe for a weight on bit to be delivered to the bit, and/or determine a spindle change to modify the toolface. The systems and methods may also send control signals to apply the spindle change and/or block velocity change to correct any detected or anticipated toolface error.

Systems and methods of controlling drilling operations including Sliding With Indexing For Toolface (SWIFT) and Variable Weight Drilling (VWD) techniques. The methods and systems may include systems and devices for controlling the drilling operations, including systems and devices capable of automatically determining drilling parameters and setting operating parameters for drilling in a wellbore. The systems and methods may also determine a change in weight on bit and/or toolface, determine a timeframe for a weight on bit to be delivered to the bit, and/or determine a spindle change to modify the toolface. The systems and methods may also send control signals to apply the spindle change and/or block velocity change to correct any detected or anticipated toolface error.

Systems and methods include a computer-implemented method for determining normalized apparent power. Drilling acoustic signals corresponding to a time domain and generated during drilling of a well. A fast Fourier transformation (FFT) is performed using the drilling acoustic signals to generate FFT data. Normalized FFT data is generated using normalization parameters and a drill string rotation rate record of a drill string used to drill the well. The drill string rotation rate is received during drilling. Normalized apparent power is determined from data points of a predetermined top percentage of the normalized FFT data within a lithological significant frequency range. The normalized apparent power is a measure of the power of the drilling acoustic signals and it is a function of the amplitude and frequency of the normalized FFT data. The lithological significant frequency range is a frequency range within which the drill sounds are more closely related with lithology.

Certain aspects and features relate to a system that includes a well tool configured to transmit an acoustic signal, detect a reflection signal, and transmit data representing the reflection signal. A processor analyzes the data to identify a pulse portion of the reflection signal, which is distinct from a reverberation portion. The processor determines a value for an attribute of the reflection signal, and executes a model to generate a first set of synthetic values for the attribute of the reflection signal and a second set of synthetic values for an impedance of a cement casing. The processor can then generate a lookup table that correlates the first set of synthetic values to the second set of synthetic values. By referencing the lookup table, processor can determine the impedance of the cement casing and alter a drilling plan or a completion plan based on the impedance of the cement casing.

In some embodiments, a method includes conveying a downhole tool in a tubing, positioned in a casing which forms an annulus between the casing and a wellbore formed in a subsurface formation, the downhole tool having a rotatable transmitter and a receiver array. The method includes performing the following until an acoustic transmission has been emitted for each of a number of defined azimuthal positions: rotating the rotatable transmitter to one of the number of defined azimuthal positions, emitting the acoustic transmission, and detecting, by the receiver array and without rotation of the downhole tool beyond a rotation threshold, an acoustic response of a number of acoustic responses that is derived from the acoustic transmission. The method further includes computationally rotating, by a processor and after detecting, data of each of the number of acoustic responses in a pre-determined direction to generate a computationally rotated multipole response.

In some embodiments, a method includes conveying a downhole tool in a tubing, positioned in a casing which forms an annulus between the casing and a wellbore formed in a subsurface formation, the downhole tool having a rotatable transmitter and a receiver array. The method includes performing the following until an acoustic transmission has been emitted for each of a number of defined azimuthal positions: rotating the rotatable transmitter to one of the number of defined azimuthal positions, emitting the acoustic transmission, and detecting, by the receiver array and without rotation of the downhole tool beyond a rotation threshold, an acoustic response of a number of acoustic responses that is derived from the acoustic transmission. The method further includes computationally rotating, by a processor and after detecting, data of each of the number of acoustic responses in a pre-determined direction to generate a computationally rotated multipole response.

Systems and methods are provided for determining a formation body wave slowness from an acoustic wave. Waveform data is determined by logging tool measuring the acoustic wave. Wave features are determined from the waveform data and a model is applied to the wave features to determine data-driven scale factors The data-driven scale factors can be used to determine a body wave slowness within a surrounding borehole environment and the body wave slowness can be used to determine formation characteristics of the borehole environment.