Import Drillholes Data¶

In [1]:

import geolime as geo

import geolime as geo

From Collar, Assay & Survey Files¶

Case 1 : With one Interval File → Assays only¶

In [3]:

collar = geo.datasets.load("rocklea_dome/collar.csv")
assay = geo.datasets.load("rocklea_dome/assay.csv")
survey = geo.datasets.load("rocklea_dome/survey.csv")
hyperspec = geo.datasets.load("rocklea_dome/hyperspec.csv")

collar = geo.datasets.load("rocklea_dome/collar.csv") assay = geo.datasets.load("rocklea_dome/assay.csv") survey = geo.datasets.load("rocklea_dome/survey.csv") hyperspec = geo.datasets.load("rocklea_dome/hyperspec.csv")

In [4]:

collar.head()

collar.head()

Out[4]:

	Hole_ID	X	Y	RL_AHD	Depth
0	RKD002	548314.8	7476791.8	467.4	45.2
1	RKD004	548095.6	7476396.0	462.3	53.0
2	RKD015	547905.0	7476800.0	470.0	41.0
3	RKD005	547505.9	7475596.0	461.6	42.4
4	RKD006	547698.1	7475588.5	458.6	42.5

In [5]:

assay.head()

assay.head()

Out[5]:

	Hole_ID	From	To	Sample_ID	Fe	Fe2o3	P	S	SiO2	Al2O3	MnO	Mn	CaO	K2O	MgO	Na2O	TiO2	LOI	LOI_100
0	RKC001	35.0	36.0	36.0	0.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0.0
1	RKC001	36.0	37.0	37.0	0.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0.0
2	RKC001	37.0	38.0	38.0	0.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0.0
3	RKC001	38.0	39.0	39.0	0.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0.0
4	RKC001	39.0	40.0	40.0	0.0	0	0	0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0.0

In [6]:

survey.head()

survey.head()

Out[6]:

	Hole_ID	Distance	Azi_mag	Dip
0	RKD002	0	0	-90
1	RKD015	0	0	-90
2	RKD005	0	0	-90
3	RKD006	0	0	-90
4	RKD004	0	0	-90

In [7]:

dh = geo.create_drillholes(
    name="RCK", 
    collar=collar, 
    assays=assay, 
    survey=survey,
    method="Tangential",
    dip_convention="NEGATIVE"
)

dh = geo.create_drillholes( name="RCK", collar=collar, assays=assay, survey=survey, method="Tangential", dip_convention="NEGATIVE" )

2023-10-23 11:27:31,167 [INFO] GeoLime Project - |GEOLIME|.drillholes_api.py : Following mapping has been identified: {
    "HOLEID": "Hole_ID",
    "X_COLLAR": "X",
    "Y_COLLAR": "Y",
    "Z_COLLAR": "RL_AHD",
    "AZIMUTH": "Azi_mag",
    "DEPTH_SURVEY": "Distance",
    "DIP": "Dip",
    "FROM": "From",
    "TO": "To"
}

In [8]:

geo.plot(dh, property="Fe", agg_method="mean", width=650, height=400)

geo.plot(dh, property="Fe", agg_method="mean", width=650, height=400)

Case 2 : With multiple Interval Files → Assays & HyperSpectral¶

In [9]:

dh = geo.create_drillholes(
    name="RCK", 
    collar=collar, 
    assays=[assay, hyperspec], 
    survey=survey,
    method="Tangential",
    dip_convention="NEGATIVE"
)

dh = geo.create_drillholes( name="RCK", collar=collar, assays=[assay, hyperspec], survey=survey, method="Tangential", dip_convention="NEGATIVE" )

2023-10-23 11:27:40,950 [INFO] GeoLime Project - |GEOLIME|.drillholes_api.py : Following mapping has been identified: {
    "HOLEID": "Hole_ID",
    "X_COLLAR": "X",
    "Y_COLLAR": "Y",
    "Z_COLLAR": "RL_AHD",
    "AZIMUTH": "Azi_mag",
    "DEPTH_SURVEY": "Distance",
    "DIP": "Dip",
    "FROM": "From",
    "TO": "To"
}

In [10]:

geo.plot(dh, property="Fe", agg_method="mean", width=400, height=650)

geo.plot(dh, property="Fe", agg_method="mean", width=400, height=650)

From A Desurveyed File¶

In [11]:

desurveyed_df = geo.datasets.load("rocklea_dome/desurveyed_dh.csv")

desurveyed_df = geo.datasets.load("rocklea_dome/desurveyed_dh.csv")

In [12]:

desurveyed_df.head()

desurveyed_df.head()

Out[12]:

	FROM	TO	HOLEID	X_COLLAR	Y_COLLAR	Z_COLLAR	X_M	Y_M	Z_M	X_B	...	LOI	Fe_ox_ai	hem_over_goe	kaolin_abundance	kaolin_composition	wmAlsmai	wmAlsmci	carbai3pfit	carbci3pfit	Depth
0	0	1	RKC278	548001.3	7474002.1	453.5	548001.3	7474002.1	453.0	548001.3	...	NaN	0.1290	891.13	0.0374	0.999	NaN	NaN	NaN	NaN	47
1	1	2	RKC278	548001.3	7474002.1	453.5	548001.3	7474002.1	452.0	548001.3	...	NaN	0.1460	892.68	0.0269	1.006	NaN	NaN	NaN	NaN	47
2	2	3	RKC278	548001.3	7474002.1	453.5	548001.3	7474002.1	451.0	548001.3	...	NaN	0.1650	895.24	NaN	NaN	NaN	NaN	NaN	NaN	47
3	3	4	RKC278	548001.3	7474002.1	453.5	548001.3	7474002.1	450.0	548001.3	...	NaN	0.1000	893.34	NaN	NaN	0.0545	2211.83	NaN	NaN	47
4	4	5	RKC278	548001.3	7474002.1	453.5	548001.3	7474002.1	449.0	548001.3	...	NaN	0.0445	910.32	NaN	NaN	NaN	NaN	0.111	2312.89	47

5 rows × 35 columns

In [13]:

dh = geo.drillholes_from_dataframe(name="RCK", df=desurveyed_df)

dh = geo.drillholes_from_dataframe(name="RCK", df=desurveyed_df)

In [14]:

geo.plot(dh, property="Fe_ox_ai", agg_method="mean", width=400, height=650)

geo.plot(dh, property="Fe_ox_ai", agg_method="mean", width=400, height=650)

From GeoLime File¶

In [15]:

dh = geo.datasets.load("rocklea_dome/dh_hyper.geo")

dh = geo.datasets.load("rocklea_dome/dh_hyper.geo")

In [16]:

geo.plot(dh, property="Fe_pct", agg_method="mean", width=400, height=650)

geo.plot(dh, property="Fe_pct", agg_method="mean", width=400, height=650)

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Last update: 2023-10-23