Skip to content

NABORS INDUSTRIES LTD: total liabilities

Total liabilities for NABORS INDUSTRIES LTD. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NABORS INDUSTRIES LTD financial histories

What this measure means

Recognized obligations at the reporting date. The definition and scope differ from interest-bearing debt.

Exact concept: us-gaap:Liabilities. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2008-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Total liabilities in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2025-12-313,352,014,000USD2026-02-1310-K · 0001104659-26-014997
At date2024-12-313,297,963,000USD2026-02-1310-K · 0001104659-26-014997
At date2023-12-313,996,880,000USD2025-02-1310-K · 0001558370-25-000926
At date2022-12-313,514,459,000USD2024-02-1210-K · 0001558370-24-000973
At date2021-12-314,131,143,000USD2023-02-0910-K · 0001558370-23-001064
At date2020-12-313,803,780,000USD2022-02-1810-K · 0001558370-22-001407
At date2019-12-314,285,101,000USD2021-02-2410-K · 0001558370-21-001631
At date2018-12-314,698,757,000USD2020-02-2510-K · 0001558370-20-001335
At date2017-12-315,259,213,000USD2019-02-2810-K · 0001558370-19-001349
At date2016-12-314,932,220,000USD2018-03-0110-K · 0001558370-18-001382
At date2015-12-315,243,972,000USD2017-02-2810-K · 0001558370-17-001099
At date2014-12-316,944,134,000USD2016-02-2610-K · 0001104659-16-100551
At date2013-12-316,109,446,000USD2015-03-0210-K · 0001047469-15-001506
At date2012-12-316,629,717,000USD2014-03-0310-K · 0001047469-14-001701
At date2012-03-317,253,419,000USD2014-03-0310-K · 0001047469-14-001701
At date2011-12-317,241,735,000USD2013-03-0110-K · 0001104659-13-016655
At date2010-12-316,234,518,000USD2012-02-2910-K · 0001193125-12-089662
At date2009-12-315,462,711,000USD2011-03-3110-K/A · 0000950123-11-031283
At date2008-12-315,599,475,000USD2010-02-2610-K · 0000950123-10-018307

Related financial histories

Inspect the source

Entity
NABORS INDUSTRIES LTD / CIK 0001163739
Captured
2026-09-20T07:43:32.522Z
SEC response SHA-256
c442e0911eea7743497716bb20ccbe58c4f54a517408d0cc7fa2065c3277cff3

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001163739.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))