Patent classifications
G01V2210/43
Adaptive signal decomposition
A disclosed method for wellsite operations includes obtaining a spectral decomposition, of a seismic data associated with a geological formation. The spectral decomposition includes a first spectral representation generated using a first operator and a second spectral representation generated using a second operator. The method also includes determining a first characteristic of the first operator and a second characteristic of the second operator. The method further includes determining at least one acceptable operator based on the first characteristic and the second characteristic. The method also includes generating a geological model feature using the at least one acceptable operator.
SEISMIC IMAGING BY VISCO-ACOUSTIC REVERSE TIME MIGRATION
A method for generating a seismic image representing a subsurface includes receiving seismic data for the subsurface formation, including receiver wavelet data and source wavelet data. Source wavefield data are generated based on a forward modeling of the source wavelet data. Receiver wavefield data are generated that compensate for distortions in the seismic data by: applying a dispersion-only model to the receiver wavelet data to generate a first reconstructed back-propagated receiver wavefield portion, applying a dissipation-only model to the receiver wavelet data to generate a second reconstructed back-propagated receiver wavefield portion, and combining the first back-propagated receiver wavefield portion and the second back-propagated receiver wavefield portion into the receiver wavefield data. The method includes applying an imaging condition to the receiver wavefield data and the source wavefield data and generating, based on applying the imaging condition, visco-acoustic reverse time migration (VARTM) result data.
Mapping wave slowness using multi-mode semblance processing techniques
Techniques for calculating and visually presenting multiple acoustic modes that have different formation slowness are disclosed herein. The techniques include methods for receiving time-domain waveforms from adjacent formations in a borehole, processing each of the time-domain waveforms to generate frequency-domain spectrums, selecting frequency and slowness values, and predicting travel time of a mode associated with the slowness value. In some aspects, the method further includes steps for calculating a semblance difference of the frequency-domain spectrums based on the frequency value, the slowness value and the predicted travel time. Systems and computer-readable media are also provided.
Imaging subterranean features using Fourier transform interpolation of seismic data
Systems and methods for generating seismic images of subterranean features including: receiving raw seismic data of a subterranean formation; selecting a portion of the raw seismic data; transforming the selected portion of the raw seismic data from a first domain to a second domain; generating soft constraint data corresponding to the selected portion of the raw seismic data; calculating at least one weight using the generated soft constraint data; generating a weighted transformed data set by applying at least one weight to the transformed selected portion of the raw seismic data; selecting at least one data point of the generated weighted transformed data set; and removing the selected at least one data point from the weighted transformed data set to generate revised seismic data.
Fracture wave depth, borehole bottom condition, and conductivity estimation method
A method for characterizing a hydraulic fracture in a subsurface formation includes inducing a pressure change in a borehole drilled through the subsurface formation. At least one of pressure and a time derivative of pressure is measured in the borehole for a selected length of time. At least one physical parameter of at least one fracture is determined using the measured pressure and/or the time derivative of pressure. A method for characterizing hydraulic fracturing rate uses microseismic event count measured through the borehole and its real-time implementation.
Seismic mono-frequency workflow for direct gas reservoir detection
The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems for direct gas reservoir detection using frequency amplitude. One computer-implemented method includes spectrally decomposing seismic data associated with a target area into a plurality of mono-frequency volumes. Further, the method includes based on a low-frequency volume of the plurality of volumes, generating a low frequency map of the target area. Yet further, the method includes based on a high-frequency volume of the plurality of volumes, generating a high frequency map of the target area. Additionally, the method includes dividing the low frequency map by the high frequency map to generate a frequency ratio map. The method also includes using the frequency ratio map to identify a subsurface gas reservoir in the target area.
Detection and evaluation of ultrasonic subsurface backscatter
A system for estimating a property of a region of interest includes an acoustic measurement device including a transmitter configured to emit an acoustic signal having at least one selected frequency configured to penetrate a surface of a borehole in an earth formation and produce internal diffuse backscatter from earth formation material behind the surface and within the region of interest, and a receiver configured to detect return signals from the region of interest and generate return signal data. The system also includes a processing device configured to receive the return signal data, process the return signal data to identify internal diffuse backscatter data indicative of the internal diffuse backscatter, calculate one or more characteristics of the internal diffuse backscatter, and estimate a property of the region of interest based on the one or more characteristics of the internal diffuse backscatter.
Spectral analysis and machine learning to detect offset well communication using high frequency acoustic or vibration sensing
This disclosure presents a system, method, and apparatus for preventing fracture communication between wells, the system comprising: a sensor coupled to a fracking wellhead, circulating fluid line, or standpipe of a well and configured to convert acoustic vibrations in fracking fluid in the well into an electrical signal; a memory configured to store the electrical signal; a machine-learning system configured to analyze current frequency components of the electrical signal in a window of time and to identify impending fracture communication between the well and an offset well, the machine-learning system having been trained on previous frequency components of electrical signals measured during previous instances of fracture communication between wells; and a user interface configured to return a notification of the impending fracture communication to an operator of the well.
SYSTEMS AND METHODS FOR SEISMIC WELL TIE DOMAIN CONVERSION AND NEURAL NETWORK MODELING
Systems and methods are provided for seismic well tie domain conversion. In one embodiment, a process is provided to integrate well and seismic data for reservoir characterization. System configurations and processes described herein use neural networks to predict sonic well logs in the two way time (TWT) domain from measured well logs in depth, rather than predicting drift function. Embodiments are also directed to systems for reservoir characterization. Domain conversion of data includes receiving input data, preprocessing the data, and training a model to determine a length of an output sequence. The method also includes training the model for conversion of data based on at least one neural network. A sequence length prediction may be output as part of training and to perform modeling/prediction operations. The method also includes outputting sequence length in a TWT domain and output of transformed data.
Post-stack time domain image with broadened spectrum
A computer system receives a post-stack time-domain image having a first spectrum and representing one or more subsurface structures. The computer system reconstructs an increased-frequency version of the post-stack time-domain image using L0-constrained inversion and a least-squares mismatch ratio. The increased-frequency version of the post-stack time-domain image includes structural artifacts. The computer system removes the structural artifacts from the increased-frequency version of the post-stack time-domain image using singular value decomposition. The computer system combines the increased-frequency version of the post-stack time-domain image with the post-stack time-domain image using a weighting function. The computer system generates a combined version of the increased-frequency version of the post-stack time-domain image and the post-stack time-domain image. The combined version represents the one or more subsurface structures and has a second spectrum broader than the first spectrum.