FIELD: seismic data processing.
SUBSTANCE: invention relates to methods for processing and interpreting seismic data to determine tectonic faults. Seismic 3D images of the earth's crust are obtained. The resulting images are transmitted to the input of the trained neural network. At the output of the trained neural network, a binary mask of 3D seismic images is obtained with the prediction of tectonic faults. Post-processing of the obtained binary mask of 3D seismic images of tectonic faults is performed.
EFFECT: automation of the process of determining tectonic faults.
1 cl, 8 dwg
| Title | Year | Author | Number |
|---|---|---|---|
| SYSTEM FOR INTELLIGENT IDENTIFICATION OF TECTONIC FAULTS WITH THE HELP OF SEISMIC DATA ON THE BASIS OF CONVOLUTIONAL NEURAL NETWORKS | 2020 |
|
RU2746691C1 |
| INTERACTIVE IMAGE SEGMENTATION | 2023 |
|
RU2833268C1 |
| METHOD OF TRAINING A CONVOLUTION NEURAL NETWORK TO CARRY OUT TELEROENTGENOGRAM MARKINGS IN A DIRECT AND LATERAL PROJECTIONS | 2019 |
|
RU2717911C1 |
| METHOD FOR THREE-DIMENSIONAL STRUCTURAL MAPPING OF FAULT ZONES AND STRESS FIELDS OF THE SEDIMENTARY COVER OF THE EARTH'S CRUST FOR HYDROCARBON DEPOSITS | 2021 |
|
RU2790476C1 |
| METHOD OF DETERMINING RESIDUAL TISSUE OF ADRENAL CORTEX DURING ORGAN-SPARING OPERATIONS FOR PHEOCHROMOCYTOMA BASED ON ANALYSIS OF CT IMAGES USING U-NET CONVOLUTIONAL NEURAL NETWORK | 2023 |
|
RU2813154C1 |
| METHOD AND SYSTEM FOR GENERATING SYNTHETIC DATA | 2023 |
|
RU2824524C1 |
| TRAINING NEURAL NETWORKS FOR IMAGE PROCESSING USING SYNTHETIC PHOTOREALISTIC CONTAINING IMAGE SIGNS | 2018 |
|
RU2709661C1 |
| SYSTEM FOR GENERATING VIDEO WITH RECONSTRUCTED PHOTOREALISTIC 3D MODEL OF HUMAN, METHODS FOR SETTING UP AND OPERATING THIS SYSTEM | 2024 |
|
RU2834188C1 |
| METHOD FOR OBTAINING LOW-DIMENSIONAL NUMERIC REPRESENTATIONS OF SEQUENCES OF EVENTS | 2020 |
|
RU2741742C1 |
| METHOD FOR DIGITIZING A BIOLOGICAL PREPARATION OF BONE MARROW USING NEURAL NETWORKS | 2022 |
|
RU2793054C1 |
