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TETRA Technologies, Inc.: capital expenditure payments

Capital expenditure payments for TETRA Technologies, Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All TETRA Technologies, Inc. financial histories

What this measure means

Cash payments to acquire property, plant and equipment. This taxonomy concept does not capture every form of investment or acquisition.

Exact concept: us-gaap:PaymentsToAcquirePropertyPlantAndEquipment. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Capital expenditure payments in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3180,821,000USD2026-02-2510-K · 0000844965-26-000015
2024-01-012024-12-3160,680,000USD2026-02-2510-K · 0000844965-26-000015
2023-01-012023-12-3138,152,000USD2026-02-2510-K · 0000844965-26-000015
2022-01-012022-12-3140,056,000USD2025-02-2510-K · 0000844965-25-000013
2021-01-012021-12-3120,533,000USD2024-02-2710-K · 0000844965-24-000020
2020-01-012020-12-3129,386,000USD2023-02-2710-K · 0000844965-23-000009
2019-01-012019-12-31108,273,000USD2022-02-2810-K · 0000844965-22-000007
2018-01-012018-12-31141,931,000USD2021-03-0510-K · 0000844965-21-000002
2017-01-012017-12-3151,923,000USD2020-03-1610-K · 0000844965-20-000002
2016-01-012016-12-3121,066,000USD2019-03-0410-K · 0000844965-19-000003
2015-01-012015-12-31120,597,000USD2018-03-0510-K · 0000844965-18-000004
2014-01-012014-12-31131,609,000USD2017-03-0110-K · 0000844965-17-000003
2013-01-012013-12-31101,379,000USD2016-03-0410-K · 0000844965-16-000116
2012-01-012012-12-31107,524,000USD2014-03-0310-K · 0000844965-14-000022
2011-01-012011-12-31107,524,000USD2015-03-0210-K · 0000844965-15-000014
2010-01-012010-12-31107,684,000USD2013-03-0510-K/A · 0000844965-13-000031
2009-01-012009-12-31151,773,000USD2012-02-2910-K · 0000844965-12-000020
2008-01-012008-12-31-262,099,000USD2011-03-0110-K · 0000844965-11-000022

Related financial histories

Inspect the source

Entity
TETRA Technologies, Inc. / CIK 0000844965
Captured
2026-09-19T15:09:33.149Z
SEC response SHA-256
2d5a1f7ccb4bfe3ce4f9075abc781de6627721ea426bf976966b2c00d46d1168

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/0000844965.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"])))