Environmental Durability of an Optical Fiber Cable Intended for Distributed Strain Measurements in Concrete Structures

The present study investigates the environmental durability of a distributed optical fiber sensing (DOFS) cable on the market, commonly used for distributed strain measurements in reinforced concrete structures. An extensive experimental program was conducted on different types of specimens (including samples of bare DOFS cable and plain concrete specimens instrumented with this DOFS cable) that were exposed to accelerated and natural ageing (NA) conditions for different periods of up to 18 months. The instrumentation of both concrete specimens consisted of DOFS cables embedded at the center of the specimens and bonded at the concrete surface, as these two configurations are commonly deployed in the field. In these configurations, the alkalinity of the surrounding cement medium and the outdoor conditions are the main factors potentially affecting the characteristics of the DOFS component materials and the integrity of the various interfaces, and hence impacting the strain transfer process between the host structure and the core optical fiber (OF). Therefore, immersion in an alkaline solution at an elevated temperature or freeze/thaw (F/T) and immersion/drying (I/D) cycles were chosen as accelerated ageing conditions, depending on the considered configuration. Mechanical characterizations by tensile and pull-out tests were then carried out on the exposed specimens to assess the evolution of the mechanical properties of individual component materials as well as the evolution of bond properties at various interfaces (internal interfaces of the DOFS cable, and interface between the cable and the host structure) during ageing. Complementary physico-chemical characterizations were also performed to better understand the underlying degradation processes. The experimental results highlight that immersion in the alkaline solution induced a significant and rapid decrease in the bond properties at internal interfaces of the DOFS cable and at the cable/concrete interface (in the case of the embedded cable configuration), which was assigned to chemical degradation at the surface of the cable coating in contact with the solution (hydrolysis and thermal degradation of the EVA copolymer component). Meanwhile, F/T and I/D cycles showed more limited effects on the mechanical properties of the component materials and interfaces in the case of the bonded cable configuration. A comparison with the same specimens exposed to outdoor NA suggested that the chosen accelerated ageing conditions may not be totally representative of actual service conditions, but provided indications for improving the ageing protocols in future research. In the last part, an analysis of the distributed strain profiles collected during pull-out tests on instrumented concrete specimens clearly illustrated the consequences of ageing processes on the strain response of the DOFS cable.

New Insights on Characteristics of the Near-Wellbore Fractured Zone from Simulated High-Resolution Distributed Strain Sensing Data

Summary Rayleigh frequency-shift-based distributed strain sensing (RFS-based DSS) is a fiber-optic-based diagnostic technique, which can measure the strain change along the fiber. The spatial resolution of RFS-based DSS can be as low as 0.2 m, and the measuring sensitivity is less than 1 μɛ. Jin et al. (2021) presented a set of DSS data from the Hydraulic Fracture Test Site 2 project to demonstrate its potential to characterize near-wellbore fracture properties and to evaluate perforation efficiency during production and shut-in periods. Extensional strain changes are observed at locations around perforations during a shut-in period. At each perforation cluster, the observed responses of strain changes are significantly different. However, the driving mechanisms for the various observations are not clear, which hinders accurate interpretations of DSS data for near-wellbore fracture characterization. In this study, we applied a coupled flow and geomechanics model to simulate the observed DSS signals under various fractured reservoir conditions. The objective is to improve understanding of the DSS measurements and characterize near-wellbore fracture geometry. We used our in-house coupled flow and geomechanics simulator, which is developed by a combined finite-volume and finite-element method, to simulate strain responses within and near a fracture during shut-in and reopen periods. Local grid refinement was adopted around fractures and the wellbore, so that the simulated strain data can accurately represent the DSS measurements. The plane-strain condition is assumed. Numerical models with various fracture geometries and properties were constructed with representative parameters and in-situ conditions of the Permian Basin. The simulated well was shut-in for 4 days after producing 240 days, and reopened again for 1 day, following the actual field operation as shown in Jin et al. (2021). The characters of the strain changes along the fiber were analyzed and related to near-wellbore fracture properties. A novel diagnostic plot of relative strain change vs. wellbore pressure was presented to infer near-wellbore fracture characteristics. The impacts of permeability and size of the near-wellbore-stimulated region, fracture length, and near-perforation damage zone on strain responses were investigated through sensitivity analysis. The strain responses simulated by our model capture the observed signatures of field DSS measurements. During the shut-in period, clear positive strain changes are observed around the perforation locations, forming a “hump” signature. The shape of the “hump” region and peak value of each “hump” are dependent on the size and permeability of the near-wellbore fractured zone. Once the well is reopened, the strain changes decrease as the pressure drops. However, in one cycle of shut-in and reopen, the strain-pressure diagnostic plot shows path dependency. The discrepancy between the shut-in and reopen periods is highly influenced by the properties of near-wellbore fractured zones. The differences in the strain-pressure diagnostic plots can help to identify the conductive fractures. This study provides better understandings of the DSS measurements and their relations to the near-wellbore fracture properties, which is of practical importance for near-wellbore fracture characterization and completion/stimulation optimization.

Mechanistic Modeling of Distributed Strain Sensing DSS and Distributed Acoustic Sensing DAS to Assist Machine Learning Schemes Interpreting Unconventional Reservoir Datasets

The use of fiber optics in reservoir surveillance is bringing valuable insights to fracture geometry and fracture-hit identification, stage communication and perforation cluster fluid distribution in many hydraulic fracturing processes. However, given the complexity associated with field data, its interpretation is a major challenge faced by engineers and geoscientists. In this work, we propose to generate Distributed Strain/Acoustic Sensing (DSS/DAS) synthetic data of a cross-well fiber deployment that incorporate the physics governing hydraulic fracturing treatments. Our forward modeling is accurate enough to be reliably used in tandem with data-driven (machine learning) interpretation methods. The forward modeling is based on analytical and numerical solutions. The analytical solution is developed integrating two models: 2D fracture (e.g. Khristianovic-Geertsma-de Klerk known as KGD) and induced stress (e.g. Sneddon, 1946). DSS is estimated using the plane strain approach that combines calculated stresses and rock properties (e.g. Young's modulus and Poisson ratio). On the other hand, the numerical solution is implemented using the Displacement Discontinuity Method (DDM), a type of Boundary Element Method (BEM), with net pressure and/or shear stress as boundary condition. In this case, fiber gauge length concept is incorporated deriving displacement (i.e. DDM output) in space to obtain DSS values. In both methods DAS is estimated by the differentiation of DSS in time. The analytical technique considers a single fracture opening and is used in a sensitivity analysis to evaluate the impact that rock/fluid parameters can promote on strain time histories. Moreover, advanced cases including multiple fractures failing in tensile or shear mode are simulated applying the numerical technique. Results indicate that our models are able to capture typical characteristics present in field data: heart-shaped pattern from a fracture approaching the fiber, stress shadow and fracture hits. In particular, the numerical methodology captures relevant phenomenon associated with hydraulic and natural fractures interaction, and provides a solid foundation for generating accurate and rich synthetic data that can be used to support a physics-based machine learning interpretation framework. The developed forward modeling, when embedded in a classification or regression artificial intelligence framework, will be an important tool adding substantial insights related to field fracture systems that ultimately can lead to production optimization. Also, the development of specific packages (commercial or otherwise) that explicitly model both DSS and DAS, incorporating the impact of fracture opening and slippage on strain and strain rate, is still in its infancy. This paper is novel in this regard and opens up new avenues of research and applications of synthetic DAS/DSS in hydraulic fracturing processes.