🔥 Porosity of Reservoir Rocks: Why Tomography Doesn't See Everything and How to Fix It When building 3D core models, X-ray tomography is a powerful tool. However, it has a limitation: pores smaller than 20–25 μm remain "invisible." Microporosity is missed, and the final porosity values are underestimated. This is critical for mining engineers and geomechanicians: these models are used to calculate rock mass strength, open-pit wall stability, and mining parameters. An error in porosity leads to errors in calculations. A study conducted on rock samples from oil fields in the Perm Region shows how strongly this distortion depends on lithology – and how to correct it. 📊 What did the analysis of carbonate and terrigenous rocks show? ▪️ For carbonate rocks, the average porosity values (22.0% by gas and 21.4% by tomography) are statistically close – a difference of only 0.6 p.p. Tomography captures large pores well. However, a correlation between the methods appears only when porosity by tomography is ≥ 16.0%. Below this, tomography is useless for structure evaluation. ▪️ For terrigenous rocks, the picture is different: 10.8% vs. 8.7%. A statistically significant correlation appears when porosity by tomography is > 7.1%. Below this threshold, tomography is practically useless for terrigenous rocks. ❗️ Key result: tomography and gas volumetry are not competitors, but partners. Using them together with correction equations allows to: ✔️ Reconstruct "true" porosity from tomography data; ✔️ Estimate the volume of micropores (as the difference between the corrected and original value); ✔️ Build accurate 3D models for geomechanical calculations. 📋 Significance for Mining Practice: For calculating open-pit wall stability, assessing rock mass deformation properties, and designing mining operations, every tenth of a percent of porosity matters. The obtained equations allow mining engineers and geomechanicians to know precisely how much tomography underestimates porosity, rather than guessing. Simply apply the correction – and the model becomes a reliable basis for design decisions. 📖 Details – including the equations, binarization methodology, and statistics – are in the article: 🔗 Galkin V.I., Melkishev O.A., Savitsky Ya.V. Statistical analysis of determining porosity factor of oil and gas reservoir rocks using gas volumetry and X-Ray tomography methods. Mining Science and Technology (Russia). 2025;10(3):221–231. https://doi.org/10.17073/2500-0632-2024-08-299 🔔 More research – follow our Telegram channel: t.me/MinSciTech #inEnglish #MST #MiningEngineering #Geomechanics #Porosity #Core #Tomography #DigitalCore #SlopeStability #RockMassStrength