Abstract

AbstractThe Ordovician Majiagou Formation is one of the main gas‐producing strata in the Ordos Basin, China. The identification of hydrocarbon‐bearing intervals via conventional well logs is a challenging task. This study describes the litholog of Ma 5 (Member 5 of Majiagou Formation) dolostones, and then analyzes the responses of various conventional well logs to the presences of natural gas. The lithology of the gas bearing layers is dominantly of the dolomicrite to fine to medium crystalline dolomite. Natural gas can be produced from the low resistivity layers, and the dry layers are characterized by high resistivities. Neutron‐density crossovers are not sensitive to the presences of natural gas. In addition, there are no significant increases in sonic transit times in natural gas bearing layers. NMR (nuclear magnetic resonance) logs, DSI (Dipole Sonic Imager) logs and borehole image logs (XRMI) are introduced to discriminate the fluid property in Majiagou dolostone reservoirs. The gas bearing intervals have broad NMR T2 (transverse relaxation time) spectrum with tail distributions as well as large T2gm (T2 logarithmic mean values) values, and the T2 spectrum commonly display polymodal behaviors. In contrast, the dry layers and water layers have low T2gm values and very narrow T2 spectrum without tails. The gas bearing layers are characterized by low Vp/Vs ratios, low Poisson's ratios and low P‐wave impedances, therefore the fluid property can be discriminated using DSI logs, and the interpretation results show good matches with the gas test data. The apparent formation water resistivity (AFWR) spectrum can be derived from XRMI image logs by using the Archie's formula in the flushed zone. The gas bearing layers have broad apparent formation water resistivity spectrum and tail distributions compared with the dry and water layers, and also the interpretation results from the image logs exhibit good agreement with the gas test data. The fluid property in Majiagou dolostone reservoirs can be discriminated through NMR logs, DSI logs and borehole image logs. This study helps establish a predictable model for fluid property in dolostones, and have implications in dolostone reservoirs with similar geological backgrounds worldwide.

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