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Validation conductive fracture imaging with cross well strain and permanent fiber optic flow profiling

Authors:

Abstract

A novel diagnostic processing technique called Conductive Fracture Imaging (CFI) was applied to the Hydraulic Fracture Test Site-2 dataset acquired in 2019 in the Delaware Basin, USA. CFI results were delivered independently and subsequently compared to permanently installed fiber optic sensor arrays located in a Vertical Data Well and in two horizontal wells. The Boxwood 5PH is a Vertical Data Well that (VDW) provided low frequency cross-well-strain (CWS) to compare stage level CFI interpreted fracture heights. The two Horizontal wells (Boxwood 3H and Boxwood 4H) provided offset CWS.

The Boxwood 4H permanent fiber also provided in-well Distributed Acoustic Sensing (DAS) cluster flow and proppant allocation analytics, and (c) in-well dynamic strain sensing (DSS) which is used for cluster efficiency and production allocation down to the cluster level. The objective of this work is to directly benchmark CFI results with direct in-well DAS and DSS fibre optic measurements.

CFI can be applied to any downhole geophone or distributed acoustic sensing (DAS) fiber dataset. The applicability of DAS acquisitions spans permanent, wireline, and disposable fibers broadly. There are no special acquisition requirements or abnormal cost additive measures are needed beyond what is routinely employed to capture a downhole and/or DAS (microseismic &/or CWS) dataset. CFI is a novel technique that has been successfully benchmarked against a multiplicity of other more mature fiber optic diagnostics used to understand fracture geometries, cluster efficiencies, and now in-well production flow profiling. CFI provides a unique look at how cluster efficiencies vary along a respective wellbore and has the potential to be a tool to consistently map the relatively small conductive and propped portions of the massive hydraulic geometries created in modern completions. The key benefits of CFI are to:

  1. image fluid and proppant allocation down to the cluster level from any temporarily deployed downhole geophone, or fiber optic array (DAS or DSS);

  2. provide a 4-dimensional observation of the dynamic transport of fluid and proppant in the near-wellbore out into the far-field.

  3. CFI can deliver equivalent frac height estimates and in-well cluster level materials allocation from a vertical data well – saving the cost of a permanent fiber.

CFI can therefore provide materially useful data to constrain one's understanding of both the hydraulic and conductive fracture geometries. The CFI technique helps preclude the necessity of an expensive permanent fiber array to obtain equivalent in-well flow and materials allocation profiling.

CFI enables the reflection imaging of the conductive portion of hydraulic fractures using microseismic events as active sources. The explanation of the relationship of seismic reflectivity of hydraulic fractures approximated by thin fluid layers was previously discussed by Reshetnikov et. al. (2023) in SPE-212374-MS. CFI provides a high-resolution image of the inner part of a seismically active zone. It allows one to look inside a stimulated reservoir with a precision to the cluster level.

The CFI results demonstrate meaningful alignment to CWS intensity on the horizontal & vertical fiber monitors. Comparative CWS and CFI data shows the normalized positive strain change during the B4H as seen by the B3H alongside the CFI result after the B4H stimulation extracted along the B3H wellbore exhibits alignment. Similarly, CFI results exhibit suitable consistency with in-well DAS and DSS cluster efficiency and materials allocation data. The DAS in-well cluster analytics aligned extremely well with the time-lapse production phase DSS cluster level results (Ugueto et. al. URTEC-5408 [2021]). The authors observe meaningful and valid agreement between CFI and cluster level DAS and DSS results observed on the Boxwood 4H permanent fiber array.

The focus of this study is comparing the imaged conductive fractures to numerous complimentary diagnostics, such as:

  1. cross-well strain from low-frequency distributed acoustic sensing (CWS) located in both vertical and horizontal wellbores;

  2. in-well DAS monitoring of cluster performance, fluid allocation, and proppant allocation during active stimulation; and

  3. in-well DSS monitoring of cluster performance and production allocation after two time intervals during the production phase.