Koil Energy Solutions (KLNG) Operating Expenses (2010 - 2026)
Koil Energy Solutions (KLNG) recorded Operating Expenses of $7.9 million in Q1 2026, up 48.4% from $5.33 million a year earlier and up 15.2% from the prior quarter.
Koil Energy Solutions (KLNG) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Koil Energy Solutions' Operating Expenses came in at $27.01 million as of Mar 31, 2026, up 33.2% year-over-year; for FY2025, it came in at $24.42 million, up 21.0% from FY2024.
- Annual Operating Expenses has increased for four straight years, with a five-year compound annual growth rate of 17.4% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $20.18 million in FY2024 (+19.0%), $16.95 million in FY2023 (+6.1%), $15.99 million in FY2022 (+158.7%) and $6.18 million in FY2021 (-43.6%).
- The Q1 2026 figure is the highest quarterly Operating Expenses since Q4 2022.
- On a year-over-year basis, Operating Expenses has increased for nine consecutive quarters, with growth averaging 22.1% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 729.5% in Q4 2022, against a decline of 72.1% in Q2 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $6.86 million (Q4 2025), $6.83 million (Q3 2025) and $5.42 million (Q2 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Slb | 76.39 Bn | 73.50 Bn | 1.40 Bn | 324.00 Mn |
| 2 | Baker Hughes | 56.70 Bn | 19.98 Bn | 1.58 Bn | 723.00 Mn |
| 3 | TechnipFMC | 27.74 Bn | 23.88 Bn | 684.70 Mn | 2.28 Bn |
| 4 | Halliburton | 27.03 Bn | 18.79 Bn | 804.00 Mn | 4.94 Bn |
| 5 | Nov | 6.97 Bn | 1.76 Bn | 521.00 Mn | 1.04 Bn |
| 6 | Noble | 6.81 Bn | 4.74 Bn | 239.27 Mn | 689.21 Mn |
| 7 | Weatherford International | 5.95 Bn | 1.88 Bn | 333.00 Mn | 998.00 Mn |
| 8 | Transocean | 5.90 Bn | 3.61 Bn | 358.00 Mn | 812.00 Mn |
| 9 | Valaris | 5.52 Bn | 3.13 Bn | 123.70 Mn | 498.70 Mn |
| 10 | Koil Energy Solutions | 36.77 Mn | 36.77 Mn | - | - |
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 7.90 Mn |
| Dec 31, 2025 | 6.86 Mn |
| Sep 30, 2025 | 6.83 Mn |
| Jun 30, 2025 | 5.42 Mn |
| Mar 31, 2025 | 5.33 Mn |
| Dec 31, 2024 | 5.41 Mn |
| Sep 30, 2024 | 4.75 Mn |
| Jun 30, 2024 | 4.80 Mn |
| Mar 31, 2024 | 5.22 Mn |
| Dec 31, 2023 | 4.89 Mn |
| Sep 30, 2023 | 4.32 Mn |
| Jun 30, 2023 | 3.93 Mn |
| Mar 31, 2023 | 3.82 Mn |
| Dec 31, 2022 | 11.09 Mn |
| Sep 30, 2022 | 1.69 Mn |
| Jun 30, 2022 | 1.48 Mn |
| Mar 31, 2022 | 1.73 Mn |
| Dec 31, 2021 | 1.34 Mn |
| Sep 30, 2021 | 1.40 Mn |
| Jun 30, 2021 | 1.83 Mn |
Koil Energy Solutions Operating Expenses 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=operating-expenses&ticker=KLNG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KLNG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=KLNG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();