F3 demo

F3 demo, https://dataunderground.org/dataset/f3.

Interpretation data is provided by Xinming Wu, all data is big endian.

CIG’s profile photo (USTC-CIG)

# sphinx_gallery_thumbnail_path = '_static/cigvis/more_demos/070.png'

import numpy as np
import cigvis


def load_wellLog(p):
    nlog = 4
    npoints = 2121
    x = [259, 619, 339, 141]
    y = [33, 545, 704, 84]
    z = np.arange(0, 0.2 * npoints, 0.2)
    v = np.fromfile(p, np.float32).reshape(nlog, npoints)
    v = 0.5 * np.log(v)

    nodes = []
    for i in range(nlog):
        points = np.c_[np.ones(npoints) * x[i], np.ones(npoints) * y[i], z]
        nodes += cigvis.create_well_logs(points,
                                         v[i],
                                         cyclinder=False,
                                         radius_tube=[2, 5],
                                         null_value=-999.25)

    return nodes


if __name__ == '__main__':

    root = '/Volumes/T7/DATA/cigvisdata/F3/'
    seisp = root + 'seis.dat'
    saltp = root + 'salt.dat'
    hz2p = root + 'hz.dat'
    uncp = root + 'unc.dat'
    unc2p = root + 'unc2.dat'
    ni, nx, nt = 591, 951, 362
    shape = (ni, nx, nt)

    # seismic slices
    seis = np.memmap(seisp, np.float32, 'c', shape=shape)
    nodes = cigvis.create_slices(seis,
                                 pos=[ni - 2, 25, nt - 2],
                                 cmap='gray',
                                 clim=[-2.0, 1.5])

    # salt (geologic body)
    salt = np.memmap(saltp, np.float32, 'c', shape=shape)
    nodes += cigvis.create_bodies(salt, 0.0, 0.0, color='cyan')

    # hrizon (surface)
    hz2 = np.fromfile(hz2p, np.float32).reshape(ni, nx)
    nodes += cigvis.create_surfaces([hz2], value_type='yellow')

    # displacement field of unconformity (volume)
    unc = np.fromfile(uncp, np.float32).reshape(shape).astype(np.float32)
    # unconformity (surface)
    unc2 = np.fromfile(unc2p, np.float32).reshape(ni, nx).astype(np.float32)
    nodes += cigvis.create_surfaces([unc2])

    # well logs
    nodes += load_wellLog(root + 'logs.dat')

    # fault skin
    nodes += cigvis.create_fault_skin(root + 'skins/',
                                      endian='>',
                                      values_type='likelihood')

    nodes += cigvis.create_points(np.array([[192, 634.1855, 32.3816], [192, 616.5631, 139.5132], [192, 600.3925, 220.0604]]), r=4, color="cyan")

    cigvis.plot3D(
        nodes,
        view=cigvis.Plot3DView(
            azimuth=-65.0,
            elevation=22.0,
            fov=15.0,
            axis_scales=(1, 1, 1.7),
            zoom_factor=1.4,
        ),
        save=cigvis.Plot3DSave('example.png')
    )