Abstract:
The present disclosure includes a method for suppressing 4D noise. The method includes calculating a first similarity map based on the similarity of one of one or more first 3D images and a second 3D image. The first and second 3D images are derived from first and second surveys, respectively. The method also includes calculating a second similarity map based on the similarity of one of the one or more first 3D images and a third 3D image, which is derived from the second survey. The method also includes calculating a third similarity map based on the similarity of first and second 4D images, which are based on differences between the 3D images. The method also includes generating a composite 4D image based at least on the first, second, and third similarity maps. The present disclosure may also include associated systems and apparatus.
Abstract:
Computing device, computer instructions and method for calculating an image of a subsurface based on least square migration and image de-convolution using a matching operator F. The method includes receiving seismic data d; computing a first image m of the subsurface based on the seismic data d; computing a second image h of the subsurface based on the first image m; applying a transform operation to the first and second images m and h to obtain a first transform of the first image and a second transform of the second image; calculating the matching operator F by matching the first transform of the first image to the second transform of the second image; and generating an updated image mupdated of the subsurface based on the matching operator F and the first transform of the first image.
Abstract:
In accordance with some embodiments of the present disclosure, systems and methods for estimating repeatability using base data are disclosed. The method includes obtaining data corresponding to a survey of an exploration area, where the data includes a plurality of traces associated with the exploration area, and an acquisition metric associated with each trace of the plurality of traces. The method also includes grouping the plurality of traces into a plurality of bins, the plurality of bins based on the acquisition metrics. The method further includes calculating an acquisition repeatability metric for each pair of traces in each bin based on the acquisition metrics, and calculating a seismic repeatability metric for each pair of traces in each bin.
Abstract:
The present disclosure includes a method for suppressing 4D noise. The method includes calculating a first similarity map based on the similarity of one of one or more first 3D images and a second 3D image. The first and second 3D images are derived from first and second surveys, respectively. The method also includes calculating a second similarity map based on the similarity of one of the one or more first 3D images and a third 3D image, which is derived from the second survey. The method also includes calculating a third similarity map based on the similarity of first and second 4D images, which are based on differences between the 3D images. The method also includes generating a composite 4D image based at least on the first, second, and third similarity maps. The present disclosure may also include associated systems and apparatus.
Abstract:
A non-blended dataset related to a same surveyed area as a blended dataset is used to deblend the blended dataset. The non-blended dataset may be used to calculate a model dataset emulating the blended dataset, or may be transformed in a model domain and used to derive sparseness weights, model domain masking, scaling or shaping functions used to deblend the blended dataset.
Abstract:
A method and apparatus for noise attenuation. The method includes receiving seismic data associated with at least two vintages (di, dj) collected for a same subsurface, wherein the first and second vintages (di, dj) are taken at different times; calculating a set of filters (fi, fj) that minimizes an energy function (E), wherein the energy function (E) includes a term representing a 4D difference between the first and second vintages (di, dj); calculating primaries (pi, pj) corresponding to the first and second vintages (di, dj) based on the set of (fi, fj); and calculating a 4D difference (Δij) based on the primaries (pi, pj). The 4D difference (Δij) is minimized.