Petrophysical Interpretation Patents: Leaders & Filing Trends 2026
- 23 families from the leading assignee against a fifth-place mark of 17 and a tenth-place mark of 6 — a steep drop-off rather than an even spread across the 30 ranked companies.
- Filing grew 33% from 2021 to 2024 (3 to 4 records), the only clean multi-year comparison the data supports once the post-2024 publication lag is set aside.
- G01V and E21B dominate the claim space at 68.8% and 55.2% of the 154 records respectively, while G06N-tagged AI-based approaches sit at just 1.9%.
Filing growth compares 2021 (3 records) with 2024 (4) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field.
What this landscape covers
This dataset tracks patent families filed against petrophysical interpretation, water saturation modelling and shaly sand analysis, cross-referenced with the specific technical levers used to build those models: saturation exponent, cation exchange capacity, the dual water model, porosity cutoffs, formation resistivity factor and log-core calibration. It spans records published between 2015 and 2026, with 154 total records and a 30-company assignee ranking behind them.
The subject matter sits at the intersection of wireline logging hardware and the interpretive models run on the data it produces, which is why geophysics (G01V) and drilling (E21B) classes cover the large majority of records while data-processing and AI classes remain a minority presence.
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Filing trend and technology composition
Two views of the same 154-record set: activity by year, and where those records sit across IPC subclasses.
Filing trend, 2017-2026
Filings ran near 11-12 a year through 2017-2018 (the peak, at 12), before settling into a lower, choppier pace. The 2021-to-2024 span shows a documented 33% rise (3 to 4 records) — the only stretch clean enough to call growth. Counts for 2025 and 2026 are undercounted because publication lags filing by roughly 18 months; they should not be read as a slowdown.
IPC subclass composition
G01V (geophysics and gravity surveying) appears on 68.8% of the 154 records and E21B (earth and rock drilling) on 55.2%, confirming this is primarily a downhole-measurement and log-interpretation field. G01N (material analysis), G06F (digital data processing) and G06N (AI-based computing) each cover a single-digit-to-low-teens share, marking software and machine-learning framing as a minority but present thread. Because records carry multiple classes, these shares sum past 100% and should be read individually, not added together.
Shares are the percentage of the 154 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Petrophysical Interpretation and Saturation Models with Eureka
This page is one run against one query. Ask Eureka your own question about petrophysical interpretation and saturation models and every answer comes back with the patent numbers behind it.
Try EurekaMost-cited records in this landscape
US6470274B1 — Water saturation and sand fraction determination from borehole resistivity imaging tool, transverse induction logging and a tensorial dual water saturation model
The total porosity of the formation, the fractional volume of shale, and shale resistivity are determined for a laminated reservoir that may include dispersed shales. A tensor petrophysical model derives laminar shale volume and laminar sand conductivity from vertical and horizontal conductivities taken from multi-component induction log data, while NMR data supplies measurements of total clay-bound water and the clay-bound water held specifically in shale.Filed by Baker Hughes Incorporated, granted 2002-10-22; cited 124 times within this corpus.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US10677035B2 | Controlling hydrocarbon production | 597 |
| 2 | US6549879B1 | Determining optimal well locations from a 3D reservoir model | 293 |
| 3 | US20190003292A1 | Controlling hydrocarbon production | 199 |
| 4 | US6470274B1 | Water saturation and sand fraction determination from borehole resistivity imaging tool, transverse induction… | 124 |
| 5 | US5663499A | Method for estimating permeability from multi-array induction logs | 88 |
| 6 | US6493632B1 | Water saturation and sand fraction determination from borehole resistivity imaging tool, transverse induction… | 78 |
| 7 | US4916616A | Self-consistent log interpretation method | 76 |
| 8 | US6711502B2 | Water saturation and sand fraction determination from borehole resistivity imaging tool, transverse induction… | 65 |
| 9 | WO2001023829A2 | Determining optimal well locations from a 3D reservoir model | 58 |
| 10 | US4953399A | Method and apparatus for determining characteristics of clay-bearing formations | 57 |
Citation counts accumulate over time and favour older filings; treat them as a signal of influence within this searched corpus rather than of current technical importance.
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Three patterns stand out once the ranking, the trend and the class composition are read together.
A steep drop after the leader
The leading assignee holds 23 families, fifth place holds 17, and by tenth place the count is down to 6. That drop-off says the core saturation-model claim space is occupied by a small group of oilfield-service incumbents rather than spread thinly across many filers.
Modest but real growth, pre-lag
The only clean year-over-year comparison this dataset supports is 2021 to 2024, where filings rose 33% from 3 to 4 records. Anything after 2024 is still filling in behind an 18-month publication lag, so it should not be read as a decline.
Downhole measurement still anchors the field
G01V and E21B together cover the large majority of records, confirming that saturation-model claims are still framed around physical logging tools and drilling context rather than pure software. G06N-tagged AI approaches sit at only 1.9%, a small but distinct minority thread.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to petrophysical interpretation and saturation models, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Schlumberger Technology LLC | Schlumberger Limited | 12 |
| Schlumberger Technology LLC | Schlumberger Canada Limited | 9 |
| Schlumberger Canada Limited | Schlumberger Limited | 9 |
| Schlumberger Technology LLC | Schlumberger Technology Corporation | 6 |
| Schlumberger Technology Corporation | Schlumberger Canada Limited | 6 |
| Schlumberger Technology Corporation | Schlumberger Limited | 6 |
| WesternGeco LLC | WesternGeco Seismic Holdings Ltd. | 6 |
| Schlumberger Technology LLC | Prad Research and Development Limited | 4 |
Ten co-assignee pairs appear in the dataset, the strongest clustered among Schlumberger-affiliated entities filing jointly — consistent with a single corporate group registering related families under multiple legal entities rather than genuine cross-company collaboration.
Assignee landscape
The ranking covers 30 companies across the full 2015-2026 window, led by oilfield-service majors with long-standing wireline and formation-evaluation portfolios.
Largest single portfolio
The top-ranked assignee holds 23 families in this dataset, the largest single holding and a meaningful margin over fifth place at 17.
A second tier of active filers
Fifth place sits at 17 families, indicating several companies maintain sustained, comparable-sized portfolios rather than one company standing entirely alone.
Drop-off beyond the top tier
By tenth place, family counts fall to 6, marking where sustained portfolio-building gives way to smaller or opportunistic filing activity.
| Assignee | Recent year | YoY |
|---|---|---|
| Baker Hughes Holdings LLC | 0 | — |
| Schlumberger Technology LLC | 0 | -100% |
| Halliburton Energy Services, Inc. | 0 | -100% |
| Schlumberger Technology Corporation | 0 | -100% |
| ExxonMobil Oil Corporation | 0 | — |
| Schlumberger Canada Limited | 0 | -100% |
| Saudi Arabian Oil Co. (Saudi Aramco) | 0 | — |
| Schlumberger Limited | 0 | -100% |
Where to take this next
The ranking and trend point to where filing effort is concentrated and where it thins out — the next step is testing a specific claim idea against that picture.
Map a candidate claim against the leaders' portfolios
Before drafting, check whether a saturation-model claim overlaps the core 23-family leader position or sits in the thinner mid-table tier.
Explore assignee portfolios in EurekaWatch the AI-based saturation thread
G06N-tagged filings remain under 2% of records, making AI-driven saturation estimation one of the more open branches to monitor for new entrants.
Track emerging filings in EurekaCommon questions on this landscape
This dataset's assignee ranking covers 30 companies, and the leading assignee holds 23 families, well ahead of the fifth-place holder at 17 and the tenth-place holder at 6. The names behind these totals are dominated by long-established oilfield-service groups with decades of wireline and formation-evaluation filing history, several of which appear under related corporate entities. That structure means genuine white space is more likely to be found by checking specific claim elements against the leader's portfolio rather than assuming the field is fragmented.
The clean, comparable figure this dataset supports is a 33% rise in filings from 2021 to 2024, from 3 to 4 records. Filing counts for 2025 and 2026 look lower, but that is expected: publication typically lags actual filing by around 18 months, so recent years are always undercounted at the time a search is run. Read the 2021-2024 span as the reliable growth signal and treat anything after 2024 as still filling in rather than as a genuine decline.
US6470274B1 covers a tensorial dual water saturation model that derives laminar shale volume and sand conductivity from multi-component induction log data, combined with NMR-derived measurements of clay-bound water in shale and formation. It is the most-cited record in this dataset behind a small group of hydrocarbon-production patents, with 124 citations, making it a foundational reference point for laminated-reservoir saturation work. It does not block every saturation approach, but any model relying on tensorial resistivity components plus NMR clay-bound water measurement in laminated shaly sands should be checked against its specific claim language before filing.
Start with G01V, which covers 68.8% of the 154 records in this set and represents the geophysics and logging-tool side of the field, and E21B, covering 55.2%, which captures the drilling and wellbore context these models are applied in. G01N, G06F and G06N cover smaller but non-trivial shares tied to material analysis, digital processing and AI-based methods respectively. Because a single record often carries several of these classes, search across all of them together rather than relying on one class alone.
The clearest signal is the class composition: G06N-tagged AI-based approaches sit at only 1.9% of the 154 records, a small fraction compared with the 68.8% and 55.2% held by the core geophysics and drilling classes. That gap suggests AI-driven saturation-exponent estimation, automated porosity-cutoff selection, and calibration workflows for unconventional or tight-carbonate formations are comparatively under-claimed relative to the traditional resistivity- and NMR-based core of the field. Any first claim there should be checked against the leading assignees' portfolios, since incumbents with large existing holdings are the most likely to move into adjacent ground next.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.