Quick Overview¶

Here you can find some quick examples of what you can do with SEGY-SAK. For more details refer to the examples.

The library is imported as segysak and the loaded xarray objects are compatible with numpy and matplotlib.

The cropped volume from the Volve field in the North Sea (made available by Equinor) is used for this example, and all the examples and data in this documentation are available from the examples folder of the Github respository.

In [1]:

import matplotlib.pyplot as plt
import pathlib

import matplotlib.pyplot as plt import pathlib

In [2]:

V3D_path = pathlib.Path("data/volve10r12-full-twt-sub3d.sgy")
print("3D", V3D_path, V3D_path.exists())

V3D_path = pathlib.Path("data/volve10r12-full-twt-sub3d.sgy") print("3D", V3D_path, V3D_path.exists())

3D data/volve10r12-full-twt-sub3d.sgy True

Scan SEG-Y headers¶

A basic operation would be to check the text header included in the SEG-Y file. The get_segy_texthead function accounts for common encoding issues and returns the header as a text string. It is important to check the text header if you are unfamiliar with your data, it may provide important information about the contents/location of trace header values which are needed by SEGY-SAK to successfully load your data into a xarray.Dataset.

In [4]:

from segysak.segy import get_segy_texthead

get_segy_texthead(V3D_path)

from segysak.segy import get_segy_texthead get_segy_texthead(V3D_path)

Out[4]:

Text Header

C 1 SEGY OUTPUT FROM Petrel 2017.2 Saturday, June 06 2020 10:15:00
C 2 Name: ST10010ZDC12-PZ-PSDM-KIRCH-FULL-T.MIG_FIN.POST_STACK.3D.JS-017534 ÝCro
C 3
C 4 First inline: 10090 Last inline: 10150
C 5 First xline: 2150 Last xline: 2351
C 6 CRS: ED50-UTM31 ("MENTOR:ED50-UTM31:European 1950 Based UTM, Zone 31 North,
C 7 X min: 433955.09 max: 436589.56 delta: 2634.47
C 8 Y min: 6477439.46 max: 6478790.23 delta: 1350.77
C 9 Time min: -3402.00 max: -2.00 delta: 3400.00
C10 Lat min: 58.25'52.8804"N max: 58.26'37.9493"N delta: 0.00'45.0689"
C11 Long min: 1.52'7.1906"E max: 1.54'50.9616"E delta: 0.02'43.7710"
C12 Trace min: -3400.00 max: -4.00 delta: 3396.00
C13 Seismic (template) min: -58.55 max: 54.55 delta: 113.10
C14 Amplitude (data) min: -58.55 max: 54.55 delta: 113.10
C15 Trace sample format: IEEE floating point
C16 Coordinate scale factor: 100.00000
C17
C18 Binary header locations:
C19 Sample interval : bytes 17-18
C20 Number of samples per trace : bytes 21-22
C21 Trace date format : bytes 25-26
C22
C23 Trace header locations:
C24 Inline number : bytes 5-8
C25 Xline number : bytes 21-24
C26 Coordinate scale factor : bytes 71-72
C27 X coordinate : bytes 73-76
C28 Y coordinate : bytes 77-80
C29 Trace start time/depth : bytes 109-110
C30 Number of samples per trace : bytes 115-116
C31 Sample interval : bytes 117-118
C32
C33
C34
C35
C36
C37
C38
C39
C40 END EBCDIC

If you need to investigate the trace header data more deeply, then segy_header_scan can be used to report basic statistics of each byte position for a limited number of traces.

segy_header_scan returns a pandas.DataFrame. To see the full DataFrame use the pandas option_context manager.

In [5]:

from segysak.segy import segy_header_scan
import pandas as pd

scan = segy_header_scan(V3D_path)

with pd.option_context("display.max_rows", 100, "display.max_columns", 10):
    # drop byte locations where the mean is zero, these are likely empty.
    display(scan)

from segysak.segy import segy_header_scan import pandas as pd scan = segy_header_scan(V3D_path) with pd.option_context("display.max_rows", 100, "display.max_columns", 10): # drop byte locations where the mean is zero, these are likely empty. display(scan)

	byte_loc	count	mean	std	min	25%	50%	75%	max
TRACE_SEQUENCE_LINE	1	1000.0	1.005400e+02	57.831072	1.0	5.075000e+01	100.5	1.502500e+02	202.0
TRACE_SEQUENCE_FILE	5	1000.0	1.009198e+04	1.407687	10090.0	1.009100e+04	10092.0	1.009300e+04	10094.0
FieldRecord	9	1000.0	1.009198e+04	1.407687	10090.0	1.009100e+04	10092.0	1.009300e+04	10094.0
TraceNumber	13	1000.0	1.005400e+02	57.831072	1.0	5.075000e+01	100.5	1.502500e+02	202.0
EnergySourcePoint	17	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
CDP	21	1000.0	2.249540e+03	57.831072	2150.0	2.199750e+03	2249.5	2.299250e+03	2351.0
CDP_TRACE	25	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
TraceIdentificationCode	29	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
NSummedTraces	31	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
NStackedTraces	33	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
DataUse	35	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
offset	37	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
ReceiverGroupElevation	41	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceSurfaceElevation	45	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceDepth	49	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
ReceiverDatumElevation	53	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceDatumElevation	57	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceWaterDepth	61	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GroupWaterDepth	65	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
ElevationScalar	69	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
SourceGroupScalar	71	1000.0	-1.000000e+02	0.000000	-100.0	-1.000000e+02	-100.0	-1.000000e+02	-100.0
SourceX	73	1000.0	4.351992e+07	70152.496037	43396267.0	4.345933e+07	43519976.5	4.358062e+07	43641261.0
SourceY	77	1000.0	6.477772e+08	17532.885301	647744704.0	6.477622e+08	647777222.0	6.477923e+08	647809133.0
GroupX	81	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GroupY	85	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
CoordinateUnits	89	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
WeatheringVelocity	91	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SubWeatheringVelocity	93	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceUpholeTime	95	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GroupUpholeTime	97	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceStaticCorrection	99	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GroupStaticCorrection	101	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TotalStaticApplied	103	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
LagTimeA	105	1000.0	4.000000e+00	0.000000	4.0	4.000000e+00	4.0	4.000000e+00	4.0
LagTimeB	107	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
DelayRecordingTime	109	1000.0	4.000000e+00	0.000000	4.0	4.000000e+00	4.0	4.000000e+00	4.0
MuteTimeStart	111	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
MuteTimeEND	113	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TRACE_SAMPLE_COUNT	115	1000.0	8.500000e+02	0.000000	850.0	8.500000e+02	850.0	8.500000e+02	850.0
TRACE_SAMPLE_INTERVAL	117	1000.0	4.000000e+03	0.000000	4000.0	4.000000e+03	4000.0	4.000000e+03	4000.0
GainType	119	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
InstrumentGainConstant	121	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
InstrumentInitialGain	123	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
Correlated	125	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
SweepFrequencyStart	127	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SweepFrequencyEnd	129	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SweepLength	131	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SweepType	133	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
SweepTraceTaperLengthStart	135	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SweepTraceTaperLengthEnd	137	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TaperType	139	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
AliasFilterFrequency	141	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
AliasFilterSlope	143	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
NotchFilterFrequency	145	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
NotchFilterSlope	147	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
LowCutFrequency	149	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
HighCutFrequency	151	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
LowCutSlope	153	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
HighCutSlope	155	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
YearDataRecorded	157	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
DayOfYear	159	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
HourOfDay	161	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
MinuteOfHour	163	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SecondOfMinute	165	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TimeBaseCode	167	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
TraceWeightingFactor	169	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GeophoneGroupNumberRoll1	171	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GeophoneGroupNumberFirstTraceOrigField	173	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GeophoneGroupNumberLastTraceOrigField	175	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
GapSize	177	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
OverTravel	179	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
CDP_X	181	1000.0	4.351992e+07	70152.496037	43396267.0	4.345933e+07	43519976.5	4.358062e+07	43641261.0
CDP_Y	185	1000.0	6.477772e+08	17532.885301	647744704.0	6.477622e+08	647777222.0	6.477923e+08	647809133.0
INLINE_3D	189	1000.0	1.009198e+04	1.407687	10090.0	1.009100e+04	10092.0	1.009300e+04	10094.0
CROSSLINE_3D	193	1000.0	2.249540e+03	57.831072	2150.0	2.199750e+03	2249.5	2.299250e+03	2351.0
ShotPoint	197	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
ShotPointScalar	201	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TraceValueMeasurementUnit	203	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TransductionConstantMantissa	205	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TransductionConstantPower	209	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TransductionUnit	211	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
TraceIdentifier	213	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
ScalarTraceHeader	215	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceType	217	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceEnergyDirectionMantissa	219	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceEnergyDirectionExponent	223	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceMeasurementMantissa	225	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceMeasurementExponent	229	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
SourceMeasurementUnit	231	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
UnassignedInt1	233	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0
UnassignedInt2	237	1000.0	0.000000e+00	0.000000	0.0	0.000000e+00	0.0	0.000000e+00	0.0

The header report can also be reduced by filtering blank byte locations. Here we use the standard deviation std to filter away blank values which can help us to understand the composition of the data.

For instance, key values like trace UTM coordinates are located in bytes 73 for X & 77 for Y. We can also see the byte positions of the local grid for INLINE_3D in byte 189 and for CROSSLINE_3D in byte 193.

In [6]:

scan[scan["mean"] > 0]

scan[scan["mean"] > 0]

Out[6]:

	byte_loc	count	mean	std	min	25%	50%	75%	max
TRACE_SEQUENCE_LINE	1	1000.0	1.005400e+02	57.831072	1.0	5.075000e+01	100.5	1.502500e+02	202.0
TRACE_SEQUENCE_FILE	5	1000.0	1.009198e+04	1.407687	10090.0	1.009100e+04	10092.0	1.009300e+04	10094.0
FieldRecord	9	1000.0	1.009198e+04	1.407687	10090.0	1.009100e+04	10092.0	1.009300e+04	10094.0
TraceNumber	13	1000.0	1.005400e+02	57.831072	1.0	5.075000e+01	100.5	1.502500e+02	202.0
CDP	21	1000.0	2.249540e+03	57.831072	2150.0	2.199750e+03	2249.5	2.299250e+03	2351.0
CDP_TRACE	25	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
TraceIdentificationCode	29	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
DataUse	35	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
ElevationScalar	69	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
SourceX	73	1000.0	4.351992e+07	70152.496037	43396267.0	4.345933e+07	43519976.5	4.358062e+07	43641261.0
SourceY	77	1000.0	6.477772e+08	17532.885301	647744704.0	6.477622e+08	647777222.0	6.477923e+08	647809133.0
CoordinateUnits	89	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
LagTimeA	105	1000.0	4.000000e+00	0.000000	4.0	4.000000e+00	4.0	4.000000e+00	4.0
DelayRecordingTime	109	1000.0	4.000000e+00	0.000000	4.0	4.000000e+00	4.0	4.000000e+00	4.0
TRACE_SAMPLE_COUNT	115	1000.0	8.500000e+02	0.000000	850.0	8.500000e+02	850.0	8.500000e+02	850.0
TRACE_SAMPLE_INTERVAL	117	1000.0	4.000000e+03	0.000000	4000.0	4.000000e+03	4000.0	4.000000e+03	4000.0
Correlated	125	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
SweepType	133	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
TaperType	139	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
TimeBaseCode	167	1000.0	1.000000e+00	0.000000	1.0	1.000000e+00	1.0	1.000000e+00	1.0
CDP_X	181	1000.0	4.351992e+07	70152.496037	43396267.0	4.345933e+07	43519976.5	4.358062e+07	43641261.0
CDP_Y	185	1000.0	6.477772e+08	17532.885301	647744704.0	6.477622e+08	647777222.0	6.477923e+08	647809133.0
INLINE_3D	189	1000.0	1.009198e+04	1.407687	10090.0	1.009100e+04	10092.0	1.009300e+04	10094.0
CROSSLINE_3D	193	1000.0	2.249540e+03	57.831072	2150.0	2.199750e+03	2249.5	2.299250e+03	2351.0

To retreive the raw header content (values) use segy_header_scrape. Setting partial_scan=None will return the full dataframe of trace header information.

In [7]:

from segysak.segy import segy_header_scrape

scrape = segy_header_scrape(V3D_path, partial_scan=1000)
scrape

from segysak.segy import segy_header_scrape scrape = segy_header_scrape(V3D_path, partial_scan=1000) scrape

Out[7]:

	TRACE_SEQUENCE_LINE	TRACE_SEQUENCE_FILE	FieldRecord	TraceNumber	EnergySourcePoint	CDP	CDP_TRACE	TraceIdentificationCode	NSummedTraces	NStackedTraces	...	TraceIdentifier	ScalarTraceHeader	SourceType	SourceEnergyDirectionMantissa	SourceEnergyDirectionExponent	SourceMeasurementMantissa	SourceMeasurementExponent	SourceMeasurementUnit	UnassignedInt1	UnassignedInt2
0	1	10090	10090	1	0	2150	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
1	2	10090	10090	2	0	2151	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
2	3	10090	10090	3	0	2152	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
3	4	10090	10090	4	0	2153	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
4	5	10090	10090	5	0	2154	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
995	188	10094	10094	188	0	2337	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
996	189	10094	10094	189	0	2338	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
997	190	10094	10094	190	0	2339	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
998	191	10094	10094	191	0	2340	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0
999	192	10094	10094	192	0	2341	1	1	0	0	...	0	0	0	0	0	0	0	0	0	0

1000 rows × 91 columns

Load SEG-Y data¶

All SEG-Y (2D, 2D gathers, 3D & 3D gathers) are ingested into xarray.Dataset using the Xarray SEGY engine provided by segysak. The engine recognizes the '.segy' and .sgy' extensions automatically when passed to xr.open_dataset(). It is important to provide the dim_bytes_fieldsand if required theextra_bytes_fields` variables.

dim_byte_fields specifies the byte locations which determine the orthogonal geometry of your data. This could be CDP for 2D data, iline and xline for 3D data, or iline, xline and offset for pre-stack gathers over 3D data. UTM coordinates are not usually valid dimensions, because if a survey is rotated relative to the UTM grid, you do not get orthogonal dimensions.

UTM coordinates and other trace header information you require can be loaded via the extra_bytes_fields argument.

Note that the keys you use to label byte fields will be the keys of the dimensions and variables loaded into the dataset.

Since v0.5 of SEGY-SAK, the vertical dimension is always labelled as samples.

In [8]:

import xarray as xr

V3D = xr.open_dataset(
    V3D_path,
    dim_byte_fields={"iline": 189, "xline": 193},
    extra_byte_fields={"cdp_x": 73, "cdp_y": 77},
)
V3D

import xarray as xr V3D = xr.open_dataset( V3D_path, dim_byte_fields={"iline": 189, "xline": 193}, extra_byte_fields={"cdp_x": 73, "cdp_y": 77}, ) V3D

Out[8]:

<xarray.Dataset> Size: 42MB
Dimensions:  (iline: 61, xline: 202, samples: 850)
Coordinates:
  * iline    (iline) int16 122B 10090 10091 10092 10093 ... 10148 10149 10150
  * xline    (xline) int16 404B 2150 2151 2152 2153 2154 ... 2348 2349 2350 2351
  * samples  (samples) float32 3kB 4.0 8.0 12.0 ... 3.392e+03 3.396e+03 3.4e+03
Data variables:
    cdp_x    (iline, xline) int32 49kB ...
    cdp_y    (iline, xline) int32 49kB ...
    data     (iline, xline, samples) float32 42MB ...
Attributes:
    seisnc:   {"coord_scalar": -100.0, "coord_scaled": false}

xarray.Dataset

• Dimensions:
  • iline: 61
  • xline: 202
  • samples: 850
• Coordinates: (3)
  • iline
    (iline)
    int16
    10090 10091 10092 ... 10149 10150

    array([10090, 10091, 10092, 10093, 10094, 10095, 10096, 10097, 10098, 10099,
           10100, 10101, 10102, 10103, 10104, 10105, 10106, 10107, 10108, 10109,
           10110, 10111, 10112, 10113, 10114, 10115, 10116, 10117, 10118, 10119,
           10120, 10121, 10122, 10123, 10124, 10125, 10126, 10127, 10128, 10129,
           10130, 10131, 10132, 10133, 10134, 10135, 10136, 10137, 10138, 10139,
           10140, 10141, 10142, 10143, 10144, 10145, 10146, 10147, 10148, 10149,
           10150], dtype=int16)

  • xline
    (xline)
    int16
    2150 2151 2152 ... 2349 2350 2351

    array([2150, 2151, 2152, ..., 2349, 2350, 2351], dtype=int16)

  • samples
    (samples)
    float32
    4.0 8.0 12.0 ... 3.396e+03 3.4e+03

    array([   4.,    8.,   12., ..., 3392., 3396., 3400.], dtype=float32)

• Data variables: (3)
  • cdp_x
    (iline, xline)
    int32
    ...

    [12322 values with dtype=int32]

  • cdp_y
    (iline, xline)
    int32
    ...

    [12322 values with dtype=int32]

  • data
    (iline, xline, samples)
    float32
    ...

    seisnc :

    {"source_file": "data/volve10r12-full-twt-sub3d.sgy", "measurement_system": "m", "sample_rate": 4.0}

    text :

    C 1 SEGY OUTPUT FROM Petrel 2017.2 Saturday, June 06 2020 10:15:00 C 2 Name: ST10010ZDC12-PZ-PSDM-KIRCH-FULL-T.MIG_FIN.POST_STACK.3D.JS-017534 ÝCro C 3 C 4 First inline: 10090 Last inline: 10150 C 5 First xline: 2150 Last xline: 2351 C 6 CRS: ED50-UTM31 ("MENTOR:ED50-UTM31:European 1950 Based UTM, Zone 31 North, C 7 X min: 433955.09 max: 436589.56 delta: 2634.47 C 8 Y min: 6477439.46 max: 6478790.23 delta: 1350.77 C 9 Time min: -3402.00 max: -2.00 delta: 3400.00 C10 Lat min: 58.25'52.8804"N max: 58.26'37.9493"N delta: 0.00'45.0689" C11 Long min: 1.52'7.1906"E max: 1.54'50.9616"E delta: 0.02'43.7710" C12 Trace min: -3400.00 max: -4.00 delta: 3396.00 C13 Seismic (template) min: -58.55 max: 54.55 delta: 113.10 C14 Amplitude (data) min: -58.55 max: 54.55 delta: 113.10 C15 Trace sample format: IEEE floating point C16 Coordinate scale factor: 100.00000 C17 C18 Binary header locations: C19 Sample interval : bytes 17-18 C20 Number of samples per trace : bytes 21-22 C21 Trace date format : bytes 25-26 C22 C23 Trace header locations: C24 Inline number : bytes 5-8 C25 Xline number : bytes 21-24 C26 Coordinate scale factor : bytes 71-72 C27 X coordinate : bytes 73-76 C28 Y coordinate : bytes 77-80 C29 Trace start time/depth : bytes 109-110 C30 Number of samples per trace : bytes 115-116 C31 Sample interval : bytes 117-118 C32 C33 C34 C35 C36 C37 C38 C39 C40 END EBCDIC

    [10473700 values with dtype=float32]

• Indexes: (3)
  • iline
    PandasIndex

    PandasIndex(Index([10090, 10091, 10092, 10093, 10094, 10095, 10096, 10097, 10098, 10099,
           10100, 10101, 10102, 10103, 10104, 10105, 10106, 10107, 10108, 10109,
           10110, 10111, 10112, 10113, 10114, 10115, 10116, 10117, 10118, 10119,
           10120, 10121, 10122, 10123, 10124, 10125, 10126, 10127, 10128, 10129,
           10130, 10131, 10132, 10133, 10134, 10135, 10136, 10137, 10138, 10139,
           10140, 10141, 10142, 10143, 10144, 10145, 10146, 10147, 10148, 10149,
           10150],
          dtype='int16', name='iline'))

  • xline
    PandasIndex

    PandasIndex(Index([2150, 2151, 2152, 2153, 2154, 2155, 2156, 2157, 2158, 2159,
           ...
           2342, 2343, 2344, 2345, 2346, 2347, 2348, 2349, 2350, 2351],
          dtype='int16', name='xline', length=202))

  • samples
    PandasIndex

    PandasIndex(Index([   4.0,    8.0,   12.0,   16.0,   20.0,   24.0,   28.0,   32.0,   36.0,
             40.0,
           ...
           3364.0, 3368.0, 3372.0, 3376.0, 3380.0, 3384.0, 3388.0, 3392.0, 3396.0,
           3400.0],
          dtype='float32', name='samples', length=850))

• Attributes: (1)

  seisnc :

  {"coord_scalar": -100.0, "coord_scaled": false}

Visualising data¶

xarray objects use smart label based indexing techniques to retreive subsets of data. More details on xarray techniques for segysak are covered in the examples, but this demonstrates a general syntax for selecting data by label with xarray. Plotting is done by matploblib and xarray selections can be passed to normal matplotlib.pyplot functions.

In [9]:

fig, ax1 = plt.subplots(ncols=1, figsize=(15, 8))
iline_sel = 10093
V3D.data.transpose("samples", "iline", "xline", transpose_coords=True).sel(
    iline=iline_sel
).plot(yincrease=False, cmap="seismic_r")
plt.grid("grey")
plt.ylabel("TWT")
plt.xlabel("XLINE")

fig, ax1 = plt.subplots(ncols=1, figsize=(15, 8)) iline_sel = 10093 V3D.data.transpose("samples", "iline", "xline", transpose_coords=True).sel( iline=iline_sel ).plot(yincrease=False, cmap="seismic_r") plt.grid("grey") plt.ylabel("TWT") plt.xlabel("XLINE")

Out[9]:

Text(0.5, 0, 'XLINE')

Saving data to NetCDF4¶

SEGYSAK now loads data in a way that is compatable with the standard to_netcdf method of an xarray.Dataset. To output data to NetCDF4, simply specify the output file and Xarray should take care of the rest. If you have a particularly large SEG-Y file, that will not fit into memory, then you may need to chunk the dataset first prior to output. This will ensure lazy loading and output of data.

In [10]:

V3D.to_netcdf("data/V3D.nc")

V3D.to_netcdf("data/V3D.nc")

In [11]:

# Here the seismic volume to process one INLINE at a time to the NetCDF4 file.
V3D.chunk({"iline": 1, "xline": -1, "samples": -1}).to_netcdf("data/V3D_chks.nc")

# Here the seismic volume to process one INLINE at a time to the NetCDF4 file. V3D.chunk({"iline": 1, "xline": -1, "samples": -1}).to_netcdf("data/V3D_chks.nc")

Saving data to SEG-Y¶

To return data to SEG-Y after modification use the seisio accessor provided by SEGY-SAK. Unlike the to_netcdf method. Additional arguments are required by to_segy to successfuly write a SEG-Y file with appropriate header information. At a minimum, this should include byte locations for each dimension in the Dataset, but additional variables can be written to trace headers as required.

In [12]:

V3D.seisio.to_segy(
    "data/V3D-out.segy",
    trace_header_map={"cdp_x": 73, "cdp_y": 77},
    iline=189,
    xline=193,
)

V3D.seisio.to_segy( "data/V3D-out.segy", trace_header_map={"cdp_x": 73, "cdp_y": 77}, iline=189, xline=193, )