Schlumberger was granted a patent for machine-learning reservoir-fluid analysis.

{
  "signal_id": "15762048-183c-57c6-b7ed-b52fecb4e868",
  "signal_type": "patents-company",
  "signal_subtype": "patentGrant",
  "detected_at": "2026-09-30T17:09:14+00:00",
  "company": {
    "name": "SLB",
    "domain": "slb.com"
  },
  "data": {
    "cpc": [
      {
        "code": "G01N 33/2835"
      },
      {
        "code": "G01N 15/075"
      },
      {
        "code": "G01N 21/31"
      },
      {
        "code": "G01N 27/06"
      },
      {
        "code": "G01N 33/2823"
      }
    ],
    "tags": [
      "Intellectual Property",
      "Research & Development",
      "Machine Learning",
      "Oil & Gas"
    ],
    "detail": "In September 2026 Schlumberger patented a way to estimate SARA fractions during downhole fluid analysis, supporting oil and gas reservoir evaluation directly in the wellbore.",
    "summary": "Schlumberger was granted a patent for machine-learning reservoir-fluid analysis.",
    "event_at": "2026-09-29",
    "inventors": [
      {
        "name": "Shahnawaz Hossain Molla",
        "status": "unresolved",
        "is_primary": true
      },
      {
        "name": "Lalitha Venkataramanan",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/lalitha-venkataramanan"
      },
      {
        "name": "Trent Kristinn Walsh",
        "status": "resolved",
        "is_primary": false,
        "linkedin_url": "https://www.linkedin.com/in/trent-walsh-7609511b"
      }
    ],
    "event_kind": "grant_date",
    "grant_date": "2026-09-29",
    "source_url": "https://patents.google.com/patent/US12748097",
    "cpc_primary": {
      "code": "G01N 33/2835"
    },
    "patent_title": "Method of determining saturates, aromatics, resins, and asphaltene (SARA) fractions of reservoir fluid during downhole fluid analysis",
    "patent_number": "US12748097",
    "uspto_assignee": "Schlumberger Technology Corporation",
    "patent_abstract": "Systems and methods for estimating the SARA fractions of a reservoir fluid. This method uses a machine learning (ML) based model to predict the SARA fractions of a reservoir fluid. The ML models are trained using conventional laboratory data, such as fluid composition from gas chromatography, SARA measurement, Asphaltene onset pressure (AOP), etc. Reservoir fluid can be pumped from a wellbore into a downhole fluid analyzer tool. The downhole fluid analyzer tool can take measurements indicating the presence and levels of certain particles in the fluid. The measurements can be applied to the ML models to estimate SARA levels in the reservoir fluid.",
    "precision_class": "structural",
    "invention_explanation": "A machine-learning model combines laboratory fluid data with measurements from a downhole analyzer to estimate the fluid’s saturates, aromatics, resins, and asphaltenes.",
    "technologies_mentioned": [
      "machine learning",
      "downhole fluid analysis",
      "reservoir characterization",
      "SARA analysis"
    ]
  }
}

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