Preview Wellbore Tubing Records

First 100 rows

Out of roughly 470.2K rows in texas.wb_tubing. Version obs-280037916c8f.

First 100 rows of `texas.wb_tubing`, 9 columns wide
`api_county`	`api_unique`	`segment_counter`	`tubing_inches`	`tubing_frac_num`	`tubing_frac_denom`	`depth_set`	`packer_set`	`ingested_at`
001	00037	1	2	7	8	5905	null	Sept. 13, 2026, 10:01 p.m.
001	00045	1	2	3	8	1000	null	Sept. 13, 2026, 10:01 p.m.
001	00046	1	2	3	8	1000	null	Sept. 13, 2026, 10:01 p.m.
001	00070	1	2	7	8	9726	9726	Sept. 13, 2026, 10:01 p.m.
001	00071	1	2	3	8	9916	9920	Sept. 13, 2026, 10:01 p.m.
001	00072	1	2	3	8	10063	10060	Sept. 13, 2026, 10:01 p.m.
001	00078	1	2	3	8	5941	5934	Sept. 13, 2026, 10:01 p.m.
001	00084	1	2	3	8	9905	9905	Sept. 13, 2026, 10:01 p.m.
001	00087	1	2	3	8	null	null	Sept. 13, 2026, 10:01 p.m.
001	00089	1	2	3	8	10065	10026	Sept. 13, 2026, 10:01 p.m.
001	00090	1	2	3	8	9823	9820	Sept. 13, 2026, 10:01 p.m.
001	00091	1	2	3	8	9935	9932	Sept. 13, 2026, 10:01 p.m.
001	00091	2	null	null	null	null	9832	Sept. 13, 2026, 10:01 p.m.
001	00092	1	2	3	8	9897	9813	Sept. 13, 2026, 10:01 p.m.
001	00092	2	null	null	null	null	9832	Sept. 13, 2026, 10:01 p.m.
001	00092	3	null	null	null	null	9892	Sept. 13, 2026, 10:01 p.m.
001	00094	1	2	7	8	4858	null	Sept. 13, 2026, 10:01 p.m.
001	00094	2	2	3	8	null	9940	Sept. 13, 2026, 10:01 p.m.
001	00101	1	2	7	8	5022	5022	Sept. 13, 2026, 10:01 p.m.
001	00106	1	2	7	8	9996	9996	Sept. 13, 2026, 10:01 p.m.
001	00110	1	null	null	null	null	9850	Sept. 13, 2026, 10:01 p.m.
001	00111	1	2	7	8	4902	4902	Sept. 13, 2026, 10:01 p.m.
001	00112	1	2	7	8	9827	9342	Sept. 13, 2026, 10:01 p.m.
001	00112	2	null	null	null	null	9821	Sept. 13, 2026, 10:01 p.m.
001	00113	1	2	7	8	5048	5048	Sept. 13, 2026, 10:01 p.m.
001	00117	1	2	7	8	9715	9715	Sept. 13, 2026, 10:01 p.m.
001	00120	1	2	null	null	9829	null	Sept. 13, 2026, 10:01 p.m.
001	00128	1	2	3	8	6193	6193	Sept. 13, 2026, 10:01 p.m.
001	00135	1	2	3	8	9919	9867	Sept. 13, 2026, 10:01 p.m.
001	00135	2	2	3	8	null	9911	Sept. 13, 2026, 10:01 p.m.
001	00137	1	2	3	8	9830	9830	Sept. 13, 2026, 10:01 p.m.
001	00167	1	2	7	8	2453	null	Sept. 13, 2026, 10:01 p.m.
001	00240	1	2	3	8	3720	null	Sept. 13, 2026, 10:01 p.m.
001	00260	1	2	7	8	4549	4549	Sept. 13, 2026, 10:01 p.m.
001	00261	1	2	3	8	4523	4523	Sept. 13, 2026, 10:01 p.m.
001	00262	1	2	3	8	1750	null	Sept. 13, 2026, 10:01 p.m.
001	00264	1	2	3	8	4569	null	Sept. 13, 2026, 10:01 p.m.
001	00265	1	2	3	8	4550	4550	Sept. 13, 2026, 10:01 p.m.
001	00267	1	2	3	8	4450	null	Sept. 13, 2026, 10:01 p.m.
001	00270	1	2	3	8	4534	4534	Sept. 13, 2026, 10:01 p.m.
001	00273	1	2	7	8	4191	4191	Sept. 13, 2026, 10:01 p.m.
001	00274	1	2	3	8	4507	null	Sept. 13, 2026, 10:01 p.m.
001	00277	1	2	7	8	4500	null	Sept. 13, 2026, 10:01 p.m.
001	00280	1	4	1	2	4800	4800	Sept. 13, 2026, 10:01 p.m.
001	00282	1	2	3	8	4521	4521	Sept. 13, 2026, 10:01 p.m.
001	00284	1	3	1	2	4000	null	Sept. 13, 2026, 10:01 p.m.
001	00286	1	2	7	8	4498	4498	Sept. 13, 2026, 10:01 p.m.
001	00293	1	2	7	8	5180	3880	Sept. 13, 2026, 10:01 p.m.
001	00295	1	2	3	8	3429	null	Sept. 13, 2026, 10:01 p.m.
001	00305	1	2	3	8	4487	null	Sept. 13, 2026, 10:01 p.m.
001	00314	1	3	1	2	4530	4530	Sept. 13, 2026, 10:01 p.m.
001	00315	1	2	7	8	4007	null	Sept. 13, 2026, 10:01 p.m.
001	00320	1	2	3	8	4500	4500	Sept. 13, 2026, 10:01 p.m.
001	00336	1	2	3	8	4595	4595	Sept. 13, 2026, 10:01 p.m.
001	00337	1	2	7	8	4555	null	Sept. 13, 2026, 10:01 p.m.
001	00351	1	2	7	8	3052	null	Sept. 13, 2026, 10:01 p.m.
001	00458	1	2	7	8	4480	null	Sept. 13, 2026, 10:01 p.m.
001	00501	1	2	3	8	10250	10250	Sept. 13, 2026, 10:01 p.m.
001	00501	2	2	3	8	9436	9436	Sept. 13, 2026, 10:01 p.m.
001	00538	1	null	null	null	3163	null	Sept. 13, 2026, 10:01 p.m.
001	00540	1	2	7	8	3102	null	Sept. 13, 2026, 10:01 p.m.
001	00545	1	2	7	8	5713	5713	Sept. 13, 2026, 10:01 p.m.
001	00560	1	2	7	8	4496	4500	Sept. 13, 2026, 10:01 p.m.
001	00564	1	2	7	8	4430	null	Sept. 13, 2026, 10:01 p.m.
001	00567	1	2	7	8	4410	4415	Sept. 13, 2026, 10:01 p.m.
001	00571	1	2	7	8	4479	null	Sept. 13, 2026, 10:01 p.m.
001	00573	1	2	7	8	4405	null	Sept. 13, 2026, 10:01 p.m.
001	00578	1	2	3	8	4575	4575	Sept. 13, 2026, 10:01 p.m.
001	00619	1	2	7	8	9956	null	Sept. 13, 2026, 10:01 p.m.
001	00631	1	2	3	8	30	null	Sept. 13, 2026, 10:01 p.m.
001	00631	2	2	3	8	6181	null	Sept. 13, 2026, 10:01 p.m.
001	00640	1	2	3	8	8680	8730	Sept. 13, 2026, 10:01 p.m.
001	00666	1	2	3	8	8802	8802	Sept. 13, 2026, 10:01 p.m.
001	00671	1	2	null	null	8940	null	Sept. 13, 2026, 10:01 p.m.
001	00674	1	2	null	null	8806	null	Sept. 13, 2026, 10:01 p.m.
001	00708	1	2	7	8	9654	null	Sept. 13, 2026, 10:01 p.m.
001	00751	1	2	3	8	9517	null	Sept. 13, 2026, 10:01 p.m.
001	00757	1	2	7	8	7200	7200	Sept. 13, 2026, 10:01 p.m.
001	00759	1	2	3	8	9611	9611	Sept. 13, 2026, 10:01 p.m.
001	00766	1	2	3	8	8127	null	Sept. 13, 2026, 10:01 p.m.
001	00784	1	2	3	8	8700	8700	Sept. 13, 2026, 10:01 p.m.
001	00814	1	2	7	8	3000	3003	Sept. 13, 2026, 10:01 p.m.
001	00815	1	3	1	2	3888	3702	Sept. 13, 2026, 10:01 p.m.
001	00818	1	2	7	8	3699	3699	Sept. 13, 2026, 10:01 p.m.
001	00819	1	2	3	8	2256	2248	Sept. 13, 2026, 10:01 p.m.
001	00840	1	2	3	8	3862	3862	Sept. 13, 2026, 10:01 p.m.
001	00872	1	2	3	8	3396	3396	Sept. 13, 2026, 10:01 p.m.
001	00877	1	2	7	8	3834	3834	Sept. 13, 2026, 10:01 p.m.
001	00880	1	2	7	8	3555	3555	Sept. 13, 2026, 10:01 p.m.
001	00881	1	2	7	8	3024	3024	Sept. 13, 2026, 10:01 p.m.
001	00882	1	3	1	2	3865	3773	Sept. 13, 2026, 10:01 p.m.
001	00883	1	2	7	8	3155	3155	Sept. 13, 2026, 10:01 p.m.
001	00887	1	2	3	8	7730	7730	Sept. 13, 2026, 10:01 p.m.
001	00903	1	2	3	8	3890	null	Sept. 13, 2026, 10:01 p.m.
001	00918	1	4	null	null	1646	null	Sept. 13, 2026, 10:01 p.m.
001	00951	1	2	3	8	7475	null	Sept. 13, 2026, 10:01 p.m.
001	00973	1	2	3	8	3978	null	Sept. 13, 2026, 10:01 p.m.
001	00978	1	2	3	8	4039	4030	Sept. 13, 2026, 10:01 p.m.
001	01015	1	2	3	8	3144	3144	Sept. 13, 2026, 10:01 p.m.
001	01023	1	2	7	8	3004	3004	Sept. 13, 2026, 10:01 p.m.

What is in each column

Sampled, not exhaustive — enough to tell whether this is the data you want without making the database read tens of millions of rows.

`api_county`

varchar

Sampled: 50K
Distinct: 36

003 17.6K
009 5K
013 3.1K
029 3.1K
059 2.2K
049 2K
039 1.9K
051 1.9K
033 1.8K
055 1.6K
041 1.6K
025 1.3K

`api_unique`

varchar

Sampled: 50K
Distinct: 23.7K

31648 11
31655 11
31461 10
33312 10
30956 10
30874 10
30959 10
30780 10
30293 10
30078 10
31822 10
31635 10

`segment_counter`

int2

Sampled: 50K
Distinct: 4

1 49.3K
2 635
3 56
4 5

`tubing_inches`

int4

Sampled: 50K
Distinct: 15
Empty: 0.0252

2 47.1K
3 526
1 404
4 389
7 70
5 47
10 46
9 40
13 34
16 33
8 14
6 11

`tubing_frac_num`

int4

Sampled: 50K
Distinct: 11
Empty: 0.0381

3 28.2K
7 18K
1 1.6K
5 180
2 21
4 3
19 3
9 2
6 1
11 1
8 1

`tubing_frac_denom`

int4

Sampled: 50K
Distinct: 16
Empty: 0.0381

8 45.6K
2 1.3K
4 936
16 226
7 11
6 10
5 7
3 6
38 5
78 4
50 3
9 3

`depth_set`

int4

Sampled: 50K
Distinct: 10.8K
Empty: 0.0222

300 167
1200 166
1100 132
1400 125
1300 110
360 106
1150 99
340 99
1250 97
1450 86
1500 83
1080 79

`packer_set`

int4

Sampled: 50K
Distinct: 8.5K
Empty: 0.6052

1100 53
1200 32
1250 30
1400 26
500 26
1050 23
4500 23
7500 22
1150 22
4600 21
8000 20
1300 20

Take it away

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