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This release contains 18 CSV files covering 9 wells (3 each in zones 1, 2, 3) generated by two synthesis methods: a deterministic physics-based engine and a CTGAN baseline. Each row is a depth sample with gamma-ray, sonic, density, and resistivity logs, plus derived hydrostatic pressure, overburden, normal compaction trend, and pore pressure (Eaton method) as the regression target. The wells correspond to fields in the Eastern Potwar Basin (Pakistan): Missa Keswal (zone 1), Pindori (zone 2), and Joyamair / Minwal (zone 3).", "url": "https://huggingface.co/datasets/monteirot/wellbench", "sameAs": [ "https://github.com/tiagomonteiro0715/wellbench", "https://pypi.org/project/wellbench/" ], "version": "0.1.2", "datePublished": "2026-04-29", "license": "https://spdx.org/licenses/MIT.html", "creator": { "@type": "Person", "name": "Tiago Monteiro", "url": "https://github.com/tiagomonteiro0715" }, "publisher": { "@type": "Organization", "name": "wellbench contributors", "url": "https://huggingface.co/monteirot" }, "keywords": [ "benchmark", "synthetic-data", "well-log", "petrophysics", "pore-pressure", "ctgan", "physics-based-simulation", "geoscience", "tabular" ], "inLanguage": "en", "isAccessibleForFree": true, "isLiveDataset": false, "citeAs": "Monteiro, T. (2026). wellbench: synthetic well-log benchmark for pore-pressure prediction (Version 0.1.2) [Dataset]. 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