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Borehole Effect Correction in Pulsed Neutron-Neutron Logging for Formation Capture Cross-Section Determination
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The pulsed-neutron logging technique has been widely used to monitor the oil and gas saturation in oilfield development, and pulsed-neutron-neutron (PNN) logging, as one of pulsed-neutron logging methods, uses He-3 detectors to detect the thermal neutron counts decay with time downhole and extract the capture cross section (sigma) of the formation from the thermal neutron time-decay spectrum to evaluate the reservoir saturation. However, variable borehole conditions and the difference between formation and borehole media will result in the uncertainty of the borehole effects on the derived formation sigma, which will hamper the calculation of reliable hydrocarbon saturation. For this purpose, a borehole effect adaptive correction method based on image feature detection was proposed. First, the capture cross sections extracted from different moments of the thermal neutron time-decay spectrum are calculated to form the sigma matrix, which is transformed into a gray image. After that, two kinds of image segmentation methods, OTSU and fuzzy OTSU method, which can provide double segmentation thresholds, are combined to eliminate the borehole effect utilizing the non-uniformity of image brightness distribution caused by the sigma difference between borehole fluid and formation and to extract the formation-dominated region from the image. Finally, the counts of the moments in the formation region were exponentially fitted to solve the formation sigma. Test pit experiments and Monte-Carlo-simulated cases were used to verify the applicability of the proposed method under different environmental conditions. The results showed that the calculated and intrinsic formation sigma have a good correlation after the borehole effect correction by the proposed method. Moreover, the interpretation results of PNN logging from actual field examples proved the proposed method’s performance by comparing it with the completion saturation.
Society of Petrophysicists and Well Log Analysts
Title: Borehole Effect Correction in Pulsed Neutron-Neutron Logging for Formation Capture Cross-Section Determination
Description:
The pulsed-neutron logging technique has been widely used to monitor the oil and gas saturation in oilfield development, and pulsed-neutron-neutron (PNN) logging, as one of pulsed-neutron logging methods, uses He-3 detectors to detect the thermal neutron counts decay with time downhole and extract the capture cross section (sigma) of the formation from the thermal neutron time-decay spectrum to evaluate the reservoir saturation.
However, variable borehole conditions and the difference between formation and borehole media will result in the uncertainty of the borehole effects on the derived formation sigma, which will hamper the calculation of reliable hydrocarbon saturation.
For this purpose, a borehole effect adaptive correction method based on image feature detection was proposed.
First, the capture cross sections extracted from different moments of the thermal neutron time-decay spectrum are calculated to form the sigma matrix, which is transformed into a gray image.
After that, two kinds of image segmentation methods, OTSU and fuzzy OTSU method, which can provide double segmentation thresholds, are combined to eliminate the borehole effect utilizing the non-uniformity of image brightness distribution caused by the sigma difference between borehole fluid and formation and to extract the formation-dominated region from the image.
Finally, the counts of the moments in the formation region were exponentially fitted to solve the formation sigma.
Test pit experiments and Monte-Carlo-simulated cases were used to verify the applicability of the proposed method under different environmental conditions.
The results showed that the calculated and intrinsic formation sigma have a good correlation after the borehole effect correction by the proposed method.
Moreover, the interpretation results of PNN logging from actual field examples proved the proposed method’s performance by comparing it with the completion saturation.
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