Dawson Geophysical (DWSN) Total Liabilities (2010 - 2026)
Dawson Geophysical (DWSN) posted Total Liabilities of $35.29 million for Q2 2026, up 20.6% from $29.27 million a year earlier but down 14.1% from the prior quarter.
Dawson Geophysical (DWSN) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Dawson Geophysical's Total Liabilities came in at $40.2 million, up 195.8% from FY2024.
- Annual Total Liabilities shows a five-year compound annual growth rate of 26.5% (FY2020 to FY2025).
- In prior years, Dawson Geophysical's Total Liabilities was $13.59 million in FY2024 (-47.9%), $26.09 million in FY2023 (+31.3%), $19.87 million in FY2022 (+71.9%) and $11.56 million in FY2021 (-6.8%).
- Quarterly Total Liabilities has run from a low of -$1.56 million in Q2 2022 to a high of $41.07 million in Q1 2026 over five years.
- On a year-over-year basis, Total Liabilities has increased in each of the last five quarters, with growth averaging 54.4% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q4 2025, with growth of 195.8%; the weakest was Q1 2022, with a decline of 84.0%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $41.07 million (Q1 2026), $40.2 million (Q4 2025) and $25.39 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Slb | 76.39 Bn | 73.50 Bn | 1.40 Bn | 28.28 Bn |
| 2 | Baker Hughes | 56.70 Bn | 19.98 Bn | 1.58 Bn | 32.54 Bn |
| 3 | TechnipFMC | 27.74 Bn | 23.88 Bn | 684.70 Mn | 7.09 Bn |
| 4 | Halliburton | 27.03 Bn | 18.79 Bn | 804.00 Mn | 14.78 Bn |
| 5 | Nov | 6.97 Bn | 1.76 Bn | 521.00 Mn | 4.94 Bn |
| 6 | Noble | 6.81 Bn | 4.74 Bn | 239.27 Mn | 2.76 Bn |
| 7 | Weatherford International | 5.95 Bn | 1.88 Bn | 333.00 Mn | 3.31 Bn |
| 8 | Transocean | 5.90 Bn | 3.61 Bn | 358.00 Mn | 6.80 Bn |
| 9 | Valaris | 5.52 Bn | 3.13 Bn | 123.70 Mn | 2.23 Bn |
| 10 | Dawson Geophysical | 90.06 Mn | 71.83 Mn | 2.61 Mn | 35.29 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 35.29 Mn |
| Mar 31, 2026 | 41.07 Mn |
| Dec 31, 2025 | 40.20 Mn |
| Sep 30, 2025 | 25.39 Mn |
| Jun 30, 2025 | 29.27 Mn |
| Mar 31, 2025 | 14.99 Mn |
| Dec 31, 2024 | 13.59 Mn |
| Sep 30, 2024 | 11.94 Mn |
| Jun 30, 2024 | 17.21 Mn |
| Mar 31, 2024 | 30.52 Mn |
| Dec 31, 2023 | 26.09 Mn |
| Sep 30, 2023 | 19.50 Mn |
| Jun 30, 2023 | 32.14 Mn |
| Dec 31, 2022 | 19.87 Mn |
| Sep 30, 2022 | 7.44 Mn |
| Jun 30, 2022 | -1.56 Mn |
| Mar 31, 2022 | 1.63 Mn |
| Dec 31, 2021 | 11.56 Mn |
| Sep 30, 2021 | 9.27 Mn |
| Jun 30, 2021 | 9.12 Mn |
Dawson Geophysical Total Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-liabilities&ticker=DWSN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "DWSN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=DWSN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();