Effects of temperature on DAS measurements

A seismic observation using Distributed Acoustic Sensing (DAS) using seafloor cable can provide spatially high-density data for a long distance in marine areas. A seafloor seismic and tsunami observation system using an optical fiber cable off Sanriku, northeastern Japan was deployed in 1996. Short-term DAS measurements were sporadically repeated since February 2019 using spare fibers of the Sanriku system (Shinohara et al., 2022). A total measurement length is approximately 100 km. It has been concluded that measurement with a sampling frequency of 100 Hz, a ping rate of 500 Hz, gauge length of 100 m, and a spatial interval of 10 m is adequate for earthquake and tsunami observation. From March 2025, we started a continuous DAS observation to observe seismic activity. When the continuous DAS observation was commenced, we developed quasi real time data transmission system through the internet. Because a DAS measurement generates a huge mount of data per unit time and capacity of internet is limited, decimation for spatial direction is adopted. In addition, data format is converted from HDF5 to conventional seismic data exchange format in Japan (win format). An interrogator generates a HDF5 file every 30 seconds. After the file generation, the telemetry system reads the HDF5 file, and decimates data for spatial domain. Then, the data format is changed to the win format and the data are sent to the internet. In other words, data transmission is delayed for a slightly greater than 30 seconds. Data with the win format can be applied to various seismic data processing which has been developed before. To locate a hypocenter using DAS data, seismic phases in DAS data must be identified. To evaluate performance of hypocenter location using DAS records, arrival times of P- and S-waves were picked up on the computer display for local earthquakes. Every 100 channel records on DAS data and data from surrounding ordinary seismic stations were used. Location program with absolute travel times and one-dimensional P-wave velocity structure was applied. Results of location of earthquakes were evaluated by mainly using location errors. Errors of the location with DAS data were smaller than those of the location without the DAS data. Increase of arrival data for DAS records seems to be efficient to improve a resolution. However, picking up signals for all channels (seismic station) manually are costly due to a large number of channels. To expand the location method, an improved automatic pick-up program using evaluation function from conventional seismic network data by seismometers for DAS data (Horiuchi et al., 2025) was applied to the DAS data obtained by the Sanriku system. As a result, arrivals time of P, S and converted PS waves can be precisely identified with high resolution. We have a plan to locate earthquakes using all DAS channels (seismic stations) and surrounding ordinary marine and land seismic stations.

Thanks to its ability to provide dense strain rate measurements along Optical Fiber (OF) cable, the Distributed Acoustic Sensing (DAS) technique spreads over different seismic and geophysical domains. They range from exploration geophysics (Mestayer et al. 2011, Daley et al. 2013), to underground structure imaging (e.g. Ajo-Franklin et al. 2019, Cheng et al. 2021) or seismic activity and background noise monitoring (Jousset et al 2018, Nayak et al. 2021). Beyond the advantage of its dense spatial sampling and given a better understanding of its instrument response (e.g. Lindsey et al. 2020), the detection performance of these new DAS measurements also depends on its ability to precisely characterize the amplitude and phase of the seismic background noise in different environments. According to recent offshore seismic noise studies (Ugalde et al. 2021, Lior et al. 2021, Guerin et al 2022), we propose a study based on DAS recordings of the seismic background noise in an on-land quiet environment.In 2020, a temporary seismic experiment PREMISE (PREliminary MIga Seismic Experiment) was carried out on the site of the underground low noise Laboratory (LSBB, Laboratoire Souterrain Bas Bruit) at Rustrel, France, in order to study the 3D seismic wave field properties in a pretty well-known underground geological structure. During this experiment, we deployed several kilometers of different OF in the LSBB galleries in order to create a multidirectional DAS array with a total fiber length of 10.5km and several ground-coupling conditions. We reprocessed two hours of “raw” DAS data, recorded with a FEBUS A1-R instrument, with different acquisition parameters to find the best configuration for enhancing the DAS measurement Signal to Noise Ratio. The power spectral density (PSD) of these reprocessed strain time-series reveals a peak in the background noise frequency range [0.08-0.25Hz] for gauge lengths of 90m and 150m. Independently, an estimation of the local strain field has been derived by a geodetic analysis (Spudich et al 1995) of the records from the LSBB broadband seismometers antenna. The comparison of the DAS and seismometers array-derived strain PSD shows a very good agreement with the secondary microseism peak in terms of frequency band, amplitude, and the wave field polarization, especially for DAS strain records processed with gauge-length of several tens of meters.

Designs and preliminary results from a multi-year project for simultaneous Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) executed across multiple wells on a Steam-Assisted Gravity Drainage (SAGD) field in Canada is presented. Primary objectives of the project were to demonstrate prototypical execution of DAS and DTS data collection on a standard SAGD pad setup and to characterize inflow across the production zone. Challenges and learnings from this technically demanding project are explored alongside a discussion on the improving viability of continuous acoustic monitoring to augment temperature sensing commonly utilized in SAGD instrumentation design. The DTS technique employs a combination of an optoelectronics topside instrument and a downhole sensing fiber to produce a distributed temperature profile of the fiber string. The topside instrument comprises a laser light source, a fast optical detector and a combination of electrical and optical circuits to control light pulsing, and the detection and measurements of Raman backscattered light containing encoded temperature information about the temperature profile. The sensing fiber type is selected based on suitability with the topside instrument and the expected maximum operating temperature of its intended sensing environment. While DTS is compatible with both single-mode (SM) and multi-mode (MM) fiber type, MM graded-index fibers are often selected for SAGD environment due to its larger optical core size. Using a MM fiber allows for increased capture of the backscatter Raman light, a much weaker light signal than the laser light launched into the optical fiber. Temperature dependent Raman signals are extracted from the returned light and by applying the Optical Time Domain Reflectometry (OTDR) technique, which produces a temperature trace consisting of temperature magnitude matched to each unit distance along the sensing fiber. The temperature trace can vary in its spatial resolution subject to the topside instrument configuration with typical resolving resolution between 0.5 – 1.5 meters. Other general DTS sensing techniques are described in the literature (for example, Hartog (2017)) but are not described here. Some of the earliest uses of DTS in thermal enhanced oil recovery (EOR) was to monitor steam breakthrough and pump vapor locking in California's steam flood as reported by Carnahan (1999). Since then, advancement in specialty fiber optics suitable for thermal environment upwards to 300°C has enabled mainstream adoption within SAGD. Uses of DTS data has expanded to include, but not limited to, monitoring of well and steam chamber conformance, tubing and casing integrity, gas ingression and water coning. DAS is an optical interferometry technique employing an optoelectronics topside instrument and a downhole sensing fiber to detect minute changes in fiber length at each location along the fiber string. The instrument is sensitive at the pico-strain (ρε) level with a spatial resolution equal to a configurable distance referred to as the gauge length. The term "acoustic" in Distributed Acoustic Sensing broadly designates any mechanical perturbation able to alter the local state of strain anywhere along the optical fiber, be it from dynamic pressure changes, or dynamic strain (e.g. vibration). While DAS is compatible with both SM and MM fiber type, deployment alongside SM fiber types have been traditionally preferred as the laser light coherence is better preserved throughout its round-trip propagation compared to MM fiber. However, DAS with MM fiber can still be used for typical fiber lengths in SAGD wells without significant penalty in signal quality as shown in literatures (MacPhail (2016), Burke (2022). This cross-compatibility with MM fiber allows collection of DAS on existing DTS fibers deployments without further intervention. Prior to DAS adoption in oil and gas, it was predominantly deployed in defense and security application to perform parameter monitoring and ground disturbance detection. As DAS technology evolved, it was first trialed in Shell's unconventional tight gas wells in February 2009 to monitor plug setting, perforation shots and active clusters during fracking operation (Molenaar et al. 2012). In EOR application like SAGD, DAS provides an augmenting dataset correlating to production inflow phases (MacPhail et al. 2016) which would not be readily detectable in the temperature domain alone. Efforts like the one presented in this paper are underway to progress horizontal inflow profiling and inferred relative volumes which aids in understanding well productivity and efficacy of added inflow control devices (ICD). Unlike DTS, acoustic data is largely unaffected by temperature masking due to well completions. For events where insufficient temperature deviation are produced, DAS may be used to surveille for common industry challenges such as steam coning, gas ingression, loss of tubing/casing integrity and more. The emerging market segment for Carbon Capture and Underground Storage (CCUS) is poised to utilize DAS as one of the many leak detection toolkit for the injection monitoring wells.

Fiber optic measurements including Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) have been established as common tools to monitor the downhole condition during hydraulic fracturing treatment as well as during production. Several authors presented a methodology of quantitative interpretation for DAS and DTS data to estimate injected/produced fluid volume distribution among perforation clusters. The quantitative interpretation allows us to not only diagnose the stimulation efficiency but also optimize the completion design for subsequent fracturing jobs. This study investigates how completion parameters are correlated with fracturing stimulation performance based on the field application of DAS and DTS interpretation methodology. The field data from MIP-3H provided by the Marcellus Shale Energy and Environmental Laboratory is analyzed in this work. As previously presented, a DAS/DTS integrated interpretation method estimates fracture half-length distribution for each stage. In this approach, fractures are assumed to be created in a swarm pattern from each perforation cluster. We do not assign fractures only at the perforation cluster locations but assume that multiple fractures are initiated along a stage interval with much smaller spacing than cluster spacing. This fracture swarm model is supported by several field observations. Once the DAS interpretation estimates the injected fluid volume for each perforation cluster, by considering the fluid volume distribution as an input parameter for the DTS interpretation, the temperature inversion provides the half-length of each fracture. This interpretation approach allows us to estimate uniformity of the fracture half-length distribution. To statistically describe the fracture uniformity, a uniformity index is defined. The estimated uniformity index is compared with inflow rate for each stage to investigate how the uniformity of fracture distribution contributes to well performance. The inflow profile is estimated by interpreting the DTS data during production. The comparison shows that the stages with uniform fracture half-length distribution are more productive. This result implies that the stages more uniformly stimulated become more productive. By observing the relationship between the uniformity index and several completion parameters such as injection rate, total volume of injected fluid, proppant concentration and so on, we can investigate what parameter is more influential to the fracture stimulation efficiency. The statistical analysis illustrates that the uniformity of the fracture half-length distribution and high productivity are correlated with high injection rate. Based on this study, the injection rate would be one of the primary design parameters to maximize the fracturing stimulation performance in this field case. As demonstrated in this study, the evaluation of fracturing stimulation design based on the interpretation of DAS and DTS data would be an essential approach to optimize it.

The usefulness of distributed acoustic sensing (DAS) VSP data to map reservoir structures and extract rock properties is limited only by our understanding of the fidelity and characteristics of the measurement. In order to calibrate both the kinematics and dynamics of DAS VSP products, we document the correspondence of the DAS and geophones measurements for extracted slowness values, corridor stacks, amplitudes, linearity with source effort, and response to incident angle. The DAS slowness values match very well with the corresponding geophone slowness and up-scaled sonic log. The arrival times and amplitudes of the corridor stacks show a very good agreement. The average earth attenuation extracted from the first break amplitudes are nearly identical for the DAS (Q=86) and geophone (Q=88) data sets. Tests varying the source effort confirm that the DAS measurement performs linearly with seismic amplitude. We also confirm the cosine squared response of the fiber to the incident angle of the seismic wave field. These tests show that properly acquired DAS VSP data sets can be trusted for both travel times and amplitude information.

Injector well completions are typically carried out using two methods: simple and selective. The performance of injector wells has traditionally been evaluated using spinner-based injection logging tools (ILTs) or on-demand fiber optic distributed temperature and acoustic (DTS or DAS) sensing while logging the well performance every 3 months or once a year depending on the application. However, with such methods utilizing a snap shot approach, critical well performance information or possible anomalies are often missed due to measurements taken only during certain periods. Therefore, operators have explored the use of advanced fiber-optics methods such as permanent distributed temperature sensing (DTS) and permanent distributed acoustic sensing (DAS), that provide continuous, real-time measurements to enable understanding of dynamic well behavior at all times and mitigate any deferred or behavioral problems. Of relevance to this work is a vertical, injector well in a competent sandstone formation of the Heavy Oil Chichimene field in Llanos Basin, Colombia. As a first step of the fiber-optics monitoring strategy, a careful evaluation of DTS and DAS based fiber-optics methods was conducted. Based on the data analysis and operational history, DAS-based fiber optics monitoring was chosen as the most effective monitoring solution for this well. Subsequently, a proprietary DAS algorithm was developed to analyze the data and estimate the flow allocation for all the four zones. The results include waterfall acoustic energy maps, temporal flow allocation profiles and most importantly, the zonal flow allocation values. Predicted (DAS) zonal flow allocation data was compared with traditional injection logs (ILT) under different operational conditions (varied injection flow rates and valve choke settings). Based on comparable agreement between DAS and ILT data, the operator decided to replace ILT runs with DAS-based fiber optic monitoring, resulting in lower operational costs while enabling near real-time monitoring, and providing the continuous distributed data essential for the dynamic monitoring of the well. The successful application of fiber-optics monitoring to provide an injection profile in conjunction with a surface-controlled electric valve system demonstrates a significant potential to optimize the injection process in complex injector wells. Further, remotely controlling, monitoring and optimizing injection rates into the multi-segmented zones improves the service life of the injection operations, eliminates future intervention costs, and increases ultimate recovery.

Summary In recent years, distributed acoustic sensing (DAS) has gained large popularity in geophysical exploration. Special attention DAS technology receives in borehole application as vertical deployments are aligned with natural fiber optic sensitivity patterns. In many cases with proper installation of DAS systems, fiber outperforms the conventional receivers in data quality. One issue still remains as DAS measurements are single component compare to usual 3C downhole geophones. Here we propose an intuitive approach to address this problem – application of a multicomponent sources to obtain three component data with DAS. We conducted an experiment utilizing a three-component source in combination with a fiber optic cable deployed behind the casing in a vertical well at the Curtin/NGL research facility. As a source, we used a relatively simple setup of a weight drop fixed at a certain angle and impacting the ground from three different azimuths. We demonstrate the successful results in recording 3C data with fiber optic sensors and discuss the outcomes.

In this study, we used data from optical fiber-based Distributed Acoustic Sensor (DAS) and Distributed Temperature Sensor (DTS) to estimate pressure along the fiber. A machine learning workflow was developed and demonstrated using experimental datasets from gas–water flow tests conducted in a 5163-ft deep well instrumented with DAS, DTS, and four downhole pressure gauges. The workflow is successfully demonstrated on two experimental datasets, corresponding to different gas injection volumes, backpressure, injection methods, and water circulation rates. The workflow utilizes the random forest algorithm and involves a two-step process for distributed pressure prediction. In the first step, single-depth predictive modeling is performed to explore the underlying relationship between the DAS (in seven different frequency bands), DTS, and the gauge pressures at the four downhole locations. The single-depth analysis showed that the low-frequency components (< 2 Hz) of the DAS data, when combined with DTS, consistently demonstrate a superior capability in predicting pressure as compared to the higher frequency bands for both the datasets achieving an average coefficient of determination (or R2) of 0.96. This can be explained by the unique characteristic of low-frequency DAS which is sensitive to both the strain and temperature perturbations. In the second step, the DTS and the low-frequency DAS data from two gauge locations were used to predict pressures at different depths. The distributed pressure modeling achieved an average R2 of 0.95 and an average root mean squared error (RMSE) of 24 psi for the two datasets across the depths analyzed, demonstrating the distributed pressure measurement capability using the proposed workflow. A majority of the current DAS applications rely on the higher frequency components. This study presents a novel application of the low-frequency DAS combined with DTS for distributed pressure measurement.

The advent of fiber optic technology in geophysics exploration has grown in its use in the exploration, production, and monitoring of subsurface environments, revolutionizing the way data are gathered and interpreted critically to speed up decision-making and reduce expense and time. Distributed Acoustic Sensing (DAS) has been increasingly utilized to build relationships in complex geophysics environments by utilizing continuous measurement along fiber optic cables with high spatial resolution and a frequency response of up to 10 KHz. DAS, as fiber optic technology examining backscattered light from a laser emitted inside the fiber and measuring strain changes, enables the performance of subsurface imaging in terms of real-time monitoring for Vertical Seismic Profiling (VSP), reservoir monitoring, and microseismic event detection. This review examines the most widely used fiber optic cables employed for DAS acquisition, namely Single-Mode Fiber (SMF) and Multi-Mode Fiber (MMF), with the different deployments and scopes of data used in geophysics exploration. Over the years, SMF has emerged as a preferred type of fiber optic cable utilized for DAS acquisition and, in most applications examined in this review, outperformed MMF. On the other side, MMF has proven to be preferable when used to measure distributed temperature. Finally, the fiber optic cable deployment technique and acquisition parameters constitute a pivotal preliminary step in DAS data preprocessing, offering a pathway to improve imaging resolution based on DAS measurement as a future scope of work.

Summary Distributed acoustic-sensing technology is a diagnostic method that has been implemented in the oil and gas industry for flow monitoring during injection or production. One of the applications is to estimate fluid distribution during hydraulic fracturing treatment. This is an invaluable diagnostic tool for multistage fracture treatments because of the large number of parameters and high uncertainty involved in these fracture treatments. Distributed acoustic sensor (DAS) measurements are based on data extracted from a fiber-optic cable installed in a wellbore. Fiber-optic cable strain is sensitive to temperature and acoustic variations induced by fluid flow with different fluid properties and fracture geometries. These parameters are evaluated from the backscattered laser pulse through the fiber using coherent Rayleigh backscattering for DAS and Raman backscattering for distributed temperature sensing (DTS). The DAS interrogation system acquires strain response to acoustic variations along the measured depth of the wellbore for all periods of time. This study presents a method of interpretation of flow-rate distribution from acoustic signals from DAS measurements. Raw acoustic measurements are transformed into energy-attribute distribution for all necessary depth locations and time frame. It allows calculating energy for each perforation cluster location. This calculation demands proper depth-interval consideration for each perforation cluster. A depth-windowing procedure allowing location of intervals where DAS channel measurements must be integrated for each timestep is applied to all stages. Based on previous experimental and computational fluid-dynamic investigations, the correlation between acoustic signal and flow rate is applied to interpret the measured DAS data to flow distribution. In this paper, the system of equations that connects acoustic energy response with clusters flow-rate distribution during the injection period using these correlations is introduced. The solution of this system allows calculating cumulative volume for each perforation cluster on each timestep and at the end of fracture treatment. As additional verification of flow-rate distribution, the results of DAS interpretation were compared with the interpretation results of DTS. A field example is used to illustrate the interpretation procedure. From this work, it is concluded that, besides qualitative analysis, the DAS interpretation method provides a quantitative estimation of flow distribution. Based on current assumptions, the interpretation results from DAS and DTS are comparable with a satisfactory agreement. The combined DAS and DTS interpretations help in understanding cluster efficiency in multistage fracture treatments.

Seismic ambient noise analysis has become an important tool for subsurface characterization, offering a cost-effective alternative to active sources and enabling continuous monitoring. Array-based techniques such as beamforming are central to ambient noise analysis, allowing the estimation of wavefield properties such as propagation direction and phase velocity. Traditionally, beamforming has been applied either to vertical-component array data, particularly for surface-wave analysis, or to three-component (3C) seismic arrays, which allow for polarization and wave-type discrimination.More recently, distributed acoustic sensing (DAS) has emerged as a powerful tool for ambient noise studies, providing dense spatial sampling and large apertures at relatively low per-channel cost. However, DAS measurements are primarily sensitive to axial strain and can therefore be interpreted as effectively single-component observations. As a result, DAS arrays deployed along a single line cannot leverage the benefits of 3C beamforming, such as polarization analysis and wave-type identification. Conversely, sparse 3C arrays provide polarization information but are often limited in wavenumber resolution due to restricted aperture and station spacing.In this study, we develop and test a joint beamforming approach that combines DAS and 3C seismic observations in a unified framework. The joint beamformer is constructed by combining normalized beam power estimates from DAS-only and 3C-only beamforming, enhancing coherent signals that are consistent across both datasets while suppressing incoherent or aliased energy. The performance of the joint approach is evaluated using numerical simulations in layered elastic media. Systematic tests are carried out for different array geometries and station spacings to investigate their effects on aliasing, resolution, and information gain. The results show that the joint beamformer improves the stability of the results, particularly in cases where DAS-only or 3C-only beamforming suffers from aliasing or limited resolution. Finally, the method is applied to a real test dataset to demonstrate its applicability under realistic noise conditions.Our study suggests that joint DAS–3C beamforming provides a robust framework for ambient noise analysis, offering improved wavefield characterization compared to single-sensor approaches and highlighting the potential of hybrid array designs for future seismic monitoring applications

Recently, oil and gas companies started to invest in fiber optic technology to remotely monitor subsurface response to stimulation. Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) record vibration and temperature around the fiber, respectively. In this research, we introduce new seismic attributes calculated from the DAS data that could suggest cross-stage fluid communication during hydraulic fracturing. The DAS data covers the entire 28 stimulated stages of the lateral MIP-3H well close to Morgantown, WV. We calculated the energy attribute for the DAS data of the studied stages. Subsequently, a Hilbert transform is applied to the DAS data to evaluate the instantaneous frequency of each trace in the DAS. In addition, we applied a fast Fourier transform to each trace for all the SEGY files to calculate the dominant frequency with a 30 second temporal window. The dominant frequency is compared to the DTS data and energy attribute for the stages in the horizontal MIP-3H well. The DTS analysis shows that stimulation of the stages 10 causes a temperature rise in the previous stage 9; in contrast, stage 18 stimulation does not affect stage 17 temperature. We suggest that the common low frequency zone identified in instantaneous frequency and dominant frequency attributes between stages 10 and 9 is related to presence of fluid and gas that transferred cross-stage during hydraulic fracturing. The fluid and results in the frequency damping of the vibrations around the fiber. We show that the frequency attribute reveals increases detail about the stimulation than conventional signal energy attribute of the DAS data.

Accurate prediction of flow regime and flow profile in wellbore is among the main interests of production engineers in the quest of optimizing wellbore production and increasing reliability of downhole completion tools especially in SAGD projects. This study introduces a methodology for wellbore monitoring by detecting flow phase and flow regime. In order to develop this method, an advanced multi-phase flow injection experiment was designed and commissioned. A flow injection setup was developed to test distributed fiber optic sensor installation under different operating conditions, including multi-phase flow (oil, brine and gas), and flow fraction scenarios. Different signal processing methods were applied to extract meaningful features and filter the noise from the raw signals. A statistical analysis was performed to assess the trend of the driven data. Then, typical SAGD models were simulated to assess the results of experimental setup for scale-up purpose and determination of local breakthrough of steam along the well. Results showed that the Distributed Acoustic Sensing (DAS) data contains different levels of signals for each phase and flow regime. We also found that some level of uncertainties is involved in relating the flow regime and DAS information which could be resolved by improving the sensor installation procedure. In addition, the application of data-driven machine learning methods was found necessary to interpret the signal patterns. Initial results have shown that steam breakthrough along the well can be detected using real time DAS high energy/frequency signals. It can be concluded that including the DAS along with Distributed Temperature Sensing (DTS) is necessary to provide a better picture of steam conformance and SAGD wellbore monitoring. The limitations of the current experimental setup restricted further conclusions regarding the hybrid DAS and DTS application. This paper is a part of an ongoing project to address the application of the combined DAS and DTS in SAGD projects. The ultimate goal is a downhole monitoring system to oversee the flow phase, flow regime and sand ingress in thermal application. The next phase will address the required improvements for developing a flow loop to handle high temperatures, include sand production and mimic thermal operation conditions.

Fiber Optics Distributed sensing technologies are evolving in the petroleum industry with its potential applicability in many areas of surveillance. Petroleum Development Oman (PDO) is embarking upon the implementation of this technology in various assets including both Gas and Oil fields. The vision of the company is to have the Fiber Optics distributed sensing technology as a surveillance tool in the Well and Reservoir Management (WRFM) toolbox and to become, where appropriate, a key element of its cycle. In comparison to conventional surveillance, fiber optic distributed sensing requires no well intervention and thereby reducing HSSE exposure and production deferment. In addition, the installed fibers can be used for multiple applications, e.g. hydraulic fracture performance monitoring and inflow performance monitoring. Recently, PDO trialed Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) technologies utilizing both, dip-in surveys and permanent installation of fiber optics in the wells. Fiber optic implementation in PDO included a polymer flooding trial in heavy oil, high permeability clastic reservoir with a strong bottom water aquifer drive. The objective was to monitor well conformance as the polymer injection progressed. The horizontal injectors were completed with pre-drilled liner and divided into four zones, each with an independent Inflow Control Valve (ICV). The well was completed with a multi-mode (MM) fiber pumped into control lines three injectors. Real time DTS data was acquired continuously in all three wells while DAS was acquired as per the injection program in one injector. DAS and DTS data were analyzed to quantify the changes in injection profile and rate in each ICV zone. This provided timely information needed for decisions related to manipulation of the ICV valves to ensure best utilization of the polymer. Another example of fiber optics was a dip-in survey in a deep gas well with commingled production which covered stacked reservoirs. This was run in order to prove the concept of flow response on DAS/DTS signals in terms of gas flowing and liquid lifting detection. The acoustic signature observed was mainly due to gas entering the well through perforations. This was detected by DAS and DTS and allowed a qualitative inflow profile to be generated. The dip in survey proved the concept and allowed justification for the permanent installation of fiber optics behind casing. The objective of the permanent setup is to improve the sensitivity of the measurement and allow for better quantification of inflow per zone. In this paper, the approach of implementing fiber optic technologies in PDO is discussed with emphasis on value generation in the various assets. Additionally, the examples mentioned in this abstract are discussed in more details and based on the results, the way forward is described.

&amp;lt;p&amp;gt;Our understanding of subsurface processes suffers from a profound observation bias: ground-motion sensors are rare, sparse, clustered on continents and not available where they are most needed. A new seismic recording technology called distributed acoustic sensing (DAS), can transform existing telecommunication fiber-optic cables into arrays of thousands of sensors, enabling meter-scale recording over tens of kilometers of linear fiber length. DAS works in high-pressure and high-temperature environments, enabling long-term recordings of seismic signals inside reservoirs, fault zones, near active volcanoes, in deep seas or in highly urbanized areas.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this talk, we will introduce this laser-based technology and present three recent cases of study. The first experiment is in the city of Stanford, California, where DAS measurements are used to provide geotechnical information at a scale normally unattainable (i.e., for each building) with traditional geophone instrumentation. In the second study, we will show how downhole DAS passive recordings from the San Andreas Fault Observatory at Depth can be used for seismic velocity estimation. In the third research, we use DAS (in collaboration with Fujitec) to understand the ocean physics and infer seismic properties of the seafloor under a 100 km telecommunication cable.&amp;lt;/p&amp;gt;