Cores and Well Logs

Part 1, Chapter 1: Foundations and the Subsurface

Learning objectives

  • Describe what cores and the main wireline logs measure
  • Use gamma ray, resistivity, and density-neutron to identify reservoir and pay
  • Apply cutoffs to compute net pay and net-to-gross
  • Explain why logs anchor the 3D property model

Reading the Rock at a Well

A well is a pinhole view of the reservoir, but a rich one. A core is an actual cylinder of rock cut from the formation and measured in the lab for porosity, permeability, and grain properties; it is ground truth but expensive and sparse. Wireline logs are continuous measurements made by tools lowered down the borehole, cheap and present wherever a well goes. The essential logs are the gamma ray (shales are radioactive and clean sands are not, so it separates reservoir from non-reservoir), resistivity (oil and gas resist electrical current while salty brine conducts, so high resistivity flags hydrocarbons), and the density-neutron pair (which together give porosity and a gas indication).

Picking Net Pay

Combining them identifies net pay: rock that is clean (low gamma ray), porous, and hydrocarbon-bearing (high resistivity, low water saturation) above the contact. The viewer below shows a synthetic suite. Drag the gamma-ray and water-saturation cutoffs and the pay flag and net-to-gross update, exactly as a petrophysicist picks pay at a well.

Cores and well logsGRRESRHOB/NPHIpayOWCDrag the gamma-ray and water cutoffs to pick net pay and read the net-to-gross.

The shale volume comes from the gamma ray, Vsh=GRGRsandGRshaleGRsandV_{sh} = \frac{GR - GR_{sand}}{GR_{shale} - GR_{sand}}, and the water saturation from Archie's law, Sw=(aRwϕmRt)1/nS_w = \left(\frac{a,R_w}{\phi^m,R_t}\right)^{1/n}, where RtR_t is the measured resistivity. These per-well numbers are the hard data the 3D property model must honor at every well.

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