def velocity_to_density_conversion(input_object, output_object, c, d):
input_seisegy = ppp.SeiSEGY(str(input_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# twt = np.array(list(input_seisegy.depths()))
for il in input_seisegy.inlines():
input_data_inline = input_seisegy.inline(il)
output_data_inline = np.copy(input_data_inline)
for idx in range(input_seisegy.nNorth):
output_data_inline[idx] = ppp.gardner(input_data_inline[idx], c, d)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def average_to_interval(input_object, output_object):
input_seisegy = ppp.SeiSEGY(str(input_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
twt = np.array(list(input_seisegy.depths()))
for il in input_seisegy.inlines():
input_data_inline = input_seisegy.inline(il)
output_data_inline = np.copy(input_data_inline)
for idx in range(input_seisegy.nNorth):
output_data_inline[idx] = ppp.avg2int(twt, input_data_inline[idx])
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def obp_calculation(input_object, output_object):
input_seisegy = ppp.SeiSEGY(str(input_object.path))
stepDepth = input_seisegy.survey_setting.stepDepth
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# depth = np.array(list(input_seisegy.depths()))
for il in input_seisegy.inlines():
input_data_inline = input_seisegy.inline(il)
output_data_inline = np.copy(input_data_inline)
for idx in range(input_seisegy.nNorth):
output_data_inline[idx] = ppp.obp_trace(input_data_inline[idx],
stepDepth)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def eaton_calculation(obp_object, vel_object, output_object, a, b, n):
obp_seisegy = ppp.SeiSEGY(str(obp_object.path))
vel_seisegy = ppp.SeiSEGY(str(vel_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# preparation
depth = np.array(list(obp_seisegy.depths()))
vn = ppp.normal(depth, a, b)
hydrostatic = ppp.hydrostatic_trace(depth)
# actual calcualtion
for il in obp_seisegy.inlines():
obp_data_inline = obp_seisegy.inline(il)
vel_data_inline = vel_seisegy.inline(il)
output_data_inline = np.copy(obp_data_inline)
for idx in range(obp_seisegy.nNorth):
output_data_inline[idx] = ppp.eaton(
vel_data_inline[idx], vn, hydrostatic,
obp_data_inline[idx], n=n)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def bowers_calculation(obp_object, vel_object, output_object, a, b):
obp_seisegy = ppp.SeiSEGY(str(obp_object.path))
vel_seisegy = ppp.SeiSEGY(str(vel_object.path))
output_seisegy = ppp.SeiSEGY(str(output_object.path))
# actual calcualtion
for il in obp_seisegy.inlines():
obp_data_inline = obp_seisegy.inline(il)
vel_data_inline = vel_seisegy.inline(il)
output_data_inline = np.copy(obp_data_inline)
for idx in range(obp_seisegy.nNorth):
output_data_inline[idx] = ppp.bowers(vel_data_inline[idx],
obp_data_inline[idx],
1,
start_idx=-1,
a=a,
b=b,
vmax=5000,
end_idx=None)
output_seisegy.update(ppp.InlineIndex(il), output_data_inline)
def new_seis_object(self, name):
# emit status signal to MainWindow
self.status.emit("Setting up seismic data object ...")
data_path = Path(CONF.data_root) / CONF.current_survey / \
"Seismics" / ".{}".format(name)
if data_path.exists() is True:
segy_path = ""
with open(str(data_path), "r") as fl:
json_object = json.load(fl)
segy_path = json_object['path']
seis_object = ppp.SeiSEGY(segy_path)
setattr(self, "data_{}".format(name), seis_object)
# flush status bar
self.status.emit("")
def test__seisegy():
seis_cube = ppp.SeiSEGY("test/data/f3_sparse.sgy")
# test generators
assert list(seis_cube.inlines()) == list(range(200, 641, 20))
assert list(seis_cube.crlines())[-1] == 1200
assert list(seis_cube.inline_crlines())[-1] == (640, 1200)
assert list(seis_cube.depths())[-1] == 1100
# test retrieve data
first_test_cdp_data = seis_cube.data(ppp.CdpIndex((200, 700)))
assert (seis_cube.data(ppp.InlineIndex(200))[0] == \
first_test_cdp_data).all()
assert (seis_cube.data(ppp.CrlineIndex(700))[0] == \
first_test_cdp_data).all()
assert seis_cube.data(ppp.DepthIndex(1100))[0][0] == \
first_test_cdp_data[-1]
assert seis_cube.valid_cdp((199, 400)) == (200, 400)
assert str(seis_cube) == repr(seis_cube)
def create_seis_object(self, segy_path):
seis_object = ppp.SeiSEGY(segy_path)
self.tableWidget.setItem(0, 0, QTableWidgetItem("1"))
self.tableWidget.setItem(1, 0, QTableWidgetItem("1 - Floating point"))
self.tableWidget.setItem(
2, 0, QTableWidgetItem("{} ({} traces)".format(
seis_object.survey_setting.nDepth,
seis_object.survey_setting.nEast * \
seis_object.survey_setting.nNorth)))
self.tableWidget.setItem(
3, 0,
QTableWidgetItem("{} - {} (s or m)".format(
seis_object.survey_setting.startDepth * 0.001,
seis_object.survey_setting.endDepth * 0.001)))
self.tableWidget.setItem(
4, 0,
QTableWidgetItem("{} - {}".format(
seis_object.survey_setting.startInline,
seis_object.survey_setting.endInline)))
self.tableWidget.setItem(
5, 0,
QTableWidgetItem("{} - {}".format(
seis_object.survey_setting.startCrline,
seis_object.survey_setting.endCrline)))
self.nsample_spinBox.setValue(seis_object.survey_setting.nDepth)
self.start_lineEdit.setText(
str(seis_object.survey_setting.startDepth * 0.001))
self.step_lineEdit.setText(
str(seis_object.survey_setting.stepDepth * 0.001))
self.info_dict = {
"inline_range": [
seis_object.survey_setting.startInline,
seis_object.survey_setting.endInline,
seis_object.survey_setting.stepInline
],
"crline_range": [
seis_object.survey_setting.startCrline,
seis_object.survey_setting.endCrline,
seis_object.survey_setting.stepCrline
],
"z_range": [
float(seis_object.survey_setting.startDepth),
float(seis_object.survey_setting.endDepth),
float(seis_object.survey_setting.stepDepth)
]
}
def plot_seis(self, dataset_name):
data_path = Path(CONF.data_root) / CONF.current_survey / \
"Seismics" / ".{}".format(dataset_name)
# seis_object = ppp.SeisCube(str(data_path))
segy_path = ""
inDepth = None
property_type = None
with open(str(data_path), "r") as fl:
json_object = json.load(fl)
segy_path = json_object['path']
property_type = json_object['Property_Type']
inDepth = json_object['inDepth']
seis_object = ppp.SeiSEGY(segy_path)
seis_object.inDepth = inDepth
seis_object.property_type = property_type
cm = ""
if seis_object.property_type == 'Reflection':
cm = u'seismic'
elif seis_object.property_type == "Velocity":
cm = u'jet'
else:
cm = u"seismic"
# read data into a ndarray
data_cube = list()
start = time.time()
for inline in seis_object.inlines():
data_cube.append(seis_object.inline(inline))
data_cube = np.array(data_cube)
end = time.time() - start
self.statusBar().showMessage("{}ms used for reading data".format(end))
start2 = time.time()
# Create source
setattr(self, "source_{}".format(dataset_name), \
self.mayavi_widget.visualization.scene. \
mlab.pipeline.scalar_field(data_cube))
# self.source = self.mayavi_widget.visualization.scene.\
# mlab.pipeline.scalar_field(data_cube, name=dataset_name)
self.statusBar().showMessage("type {}".format(type(self.source)))
length_inline = (seis_object.survey_setting.nEast - 1) * \
seis_object.survey_setting.stepInline * \
seis_object.survey_setting.inline_bin
length_depth = (seis_object.survey_setting.nDepth - 1) * \
seis_object.survey_setting.stepDepth
scale = 0.5 * length_inline / length_depth
getattr(self, "source_{}".format(dataset_name)).spacing = [
seis_object.survey_setting.inline_bin * \
seis_object.survey_setting.stepInline,
seis_object.survey_setting.crline_bin * \
seis_object.survey_setting.stepCrline,
-seis_object.stepDepth * scale]
x_slice = self.mayavi_widget.visualization.scene.\
mlab.pipeline.image_plane_widget(
getattr(self, "source_{}".format(dataset_name)),
plane_orientation='x_axes',
slice_index=int(seis_object.survey_setting.nEast // 2),
colormap=cm,
name="inline_slice")
x_slice.module_manager.scalar_lut_manager.reverse_lut = True
y_slice = self.mayavi_widget.visualization.scene.\
mlab.pipeline.image_plane_widget(
getattr(self, "source_{}".format(dataset_name)),
plane_orientation='y_axes',
slice_index=int(seis_object.survey_setting.nNorth // 2),
colormap=cm, name="crline_slice")
y_slice.module_manager.scalar_lut_manager.reverse_lut = True
z_slice = self.mayavi_widget.visualization.scene.\
mlab.pipeline.image_plane_widget(
getattr(self, "source_{}".format(dataset_name)),
plane_orientation='z_axes',
slice_index=int(seis_object.survey_setting.nDepth // 2),
colormap=cm,
name='z_slice')
z_slice.module_manager.scalar_lut_manager.reverse_lut = True
# for axis in ['x', 'y', 'z']:
# plane = self.mayavi_widget.visualization.scene.\
# mlab.pipeline.image_plane_widget(
# self.source,
# plane_orientation='{}_axes'.format(axis),
# slice_index=100,
# colormap='Greys')
# # only slice is reversed(the actual data is not)
# plane.module_manager.scalar_lut_manager.reverse_lut = True
outline = self.mayavi_widget.visualization.scene.\
mlab.outline()
# add direction hint
self.mayavi_widget.visualization.scene.\
mlab.orientation_axes(
xlabel='inline', ylabel='crline', zlabel='depth')
ax = self.mayavi_widget.visualization.scene. \
mlab.axes(
xlabel='inline', ylabel='crline', zlabel='depth',
ranges=[
seis_object.survey_setting.startInline,
seis_object.survey_setting.endInline,
seis_object.survey_setting.startCrline,
seis_object.survey_setting.endCrline,
seis_object.survey_setting.endDepth,
seis_object.survey_setting.startDepth])
ax.axes.label_format = '%.0f'
self.mayavi_widget.visualization.scene.mlab.colorbar(
orientation='vertical', label_fmt='%.1f')
self.mayavi_widget.visualization.scene. \
mlab.show()