Distributed optical fiber monitoring intelligent interpretation method and system

By constructing a differentiable forward operator and performing online assimilation, the problem of coupled modeling of wellbore thermal and acoustic processes in existing technologies is solved, enabling robust and transferable segmented/clustered interpretations in horizontal wells of conglomerate tight oil/shale oil, and improving the early location capability of anomalies.

CN122452386APending Publication Date: 2026-07-24XINJIANG PETROLEUM ADMINISTRATION BUREAU +2
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Patent Information

Application Number
CN202610930441.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-06-26
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In the context of multi-cluster segmented fracturing in horizontal wells of conglomerate tight oil/shale oil, existing technologies struggle to stably estimate the production contribution and phase state of segments/clusters within a second-level time delay, making it impossible to accurately locate abnormal conditions in the early stages. Furthermore, they lack auditable uncertainty and cross-well mobility.

Method used

A differentiable forward operator is constructed to describe the thermal and acoustic processes in the wellbore. Physical mechanism constraints are integrated into the joint loss function in a differentiable form. The fiber optic sensing data is assimilated online, and the interpretation results of mechanism parameters, event diagnosis, and uncertainty quantification are output.

Benefits of technology

It achieves minute-level, robust, auditable, and transferable online interpretation, significantly reducing false alarms, improving location and early warning capabilities, and directly supporting critical on-site decisions such as fracturing assessment, formation contribution determination, and leakage/channeling/slug flow/water hammer.

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Abstract

The invention discloses a distributed optical fiber monitoring intelligent interpretation method and system, and belongs to the field of oil production engineering, and the method comprises the steps: constructing a differentiable forward operator for describing the thermal and acoustic process of a shaft; integrating the physical mechanism constraint into a joint loss function in a differentiable form, and optimizing a differentiable forward operator; and on the basis of the optimized differentiable forward operator, carrying out online assimilation on the preprocessed optical fiber sensing data, and outputting an interpretation result containing mechanism parameters, event diagnosis and uncertainty quantification. According to the method, coupling modeling of a shaft-formation thermal process (including convection, heat conduction, radial coupling and latent heat effect) and an acoustic process (including attenuation, dispersion, convection effect and micro boundary conditions) is realized through an explicit micro modeling method, and instrument response (DTS spectral ratio, DAS base length convolution and demodulation signals) is incorporated into a differentiable link.
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