First Real-Time Fiber Optic Surveillance and Analysis of a Bullhead Stimulation of an Extended-Reach Horizontal Lateral in a Giant Offshore Carbonate Oil Field

Injectors with intelligent well completions are installed in a geologically complex reservoir setting to inject fluid into multiple zones. For effective reservoir management, it is imperative to know the injection profile along the wellbore and to detect injection defects. Distributed Temperature Sensing (DTS) fiber installed along the length of the well provides high spatial resolution and high frequency temperature data. This paper presents a methodology to estimate zonal-level fluid injection volumes using these DTS measurements. When cold fluid is injected into a hotter reservoir, the region near the wellbore cools down. When injection ceases, the wellbore region slowly warms back to the far field geothermal temperature. The proposed methodology models heat transfer in the radial direction during this warmback period using 1-D energy equations. The model is tuned to DTS data from the warm-back using regression techniques applied independently at each depth. Only the middle time region (MTR) of the warmback is considered for the model since, at early times, we have thermal effects from adiabatic expansion and, at late times, the 1-D modeling assumption is no longer valid. This approach is analogous to the MTR concept often used in pressure transient analysis. Model parameters at each depth are related directly to the volume of fluid injected in the corresponding zone and their relative values can be used to allocate injected fluid volumes. The conventional use of the warm-back model looks at the relative rate that individual zones warm up during a shut-in following cooler water injection to estimate the relative volume of fluid injected into that particular zone. This conventional methodology considers all the data points from warm-back to fit the model. The improved method presented in this paper acknowledges that the early time region (ETR) and late time region (LTR) are not really addressed in the model. Rather it carves out the information by modeling the middle time region (MTR). An alternate approach presented looks at the asymptotic behavior of the middle-time warm-back to infer the cumulative injection volume in each zone. A few test cases are presented comparing the results of the various methodologies and the insights we gain from this analysis. Injection logging is an expensive, conventional method for injection profiling. With the help of fiber technologies and methodologies presented in the paper, we can achieve an accurate understanding of injection profiling without the need for logging. Additionally, we show a methodology where subsequent analysis of warmback at two or more shut-in times gives insight into the injection profile when the original geotherm is disturbed by prior injection or not well known.

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Advances in an Integrated Analysis Workflow of Distributed Acoustic Sensing and Distributed Temperature Sensing for Water Injection Profiling on a Horizontal Well

Mahue

Dawson

Jimenez

et al. 2022

Day 2 Tue, November 01, 2022

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This paper describes advances in an integrated analysis workflow of Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) for water injection profiling on a horizontal well, completed with Limited Entry Liners (LEL). The well is completed as an injector with Limited Entry Liner (LEL), MRC horizontal lateral made of 18 separated zones with packers, each with variable numbers of holes. DAS and DTS data were acquired on coiled tubing, over an acid stimulation period followed by a water injection period. Previous analysis of the dataset, SPE-203065, focused on DTS warm-back models and highlighted challenges in the process; the use of the DAS data was limited. Recent re-processing of the data using advanced acoustic signal processing techniques was performed to extract several flow characteristics. Both transient and steady state injection conditions were analyzed: High-definition low frequency slow strain DAS was extracted over the shut-in to injection transient to compute an initial injection velocity profile as well as a stage level injection distribution across the liners. During steady state flow, acoustic denoising algorithms were applied to the DAS data in order to generate a spectral noise log of high signal to noise ratio (SNR) for the detection of all major injection points. Video animations were generated of spectral noise logs over time, to evaluate the dynamic behavior of the injection profile from start to end. The warm-back DTS data was analyzed for a qualitative assessment of the injection Finally, a quantitative injection profile was computed, and the results were compared against a separate PLT log at both stage and nozzle levels. The results of the transient and steady state flow analysis converged and showed the highest water intake to occur over the heel-ward stages. The depths of highest rate of change in injection velocity, aligned with the strongest acoustic signals from the enhanced noise log. Inversely, the weaker acoustic outflow activities over the middle and toe sections aligned with the smaller velocity changes. The video animations showed a stable injection profile over time. The qualitative DTS analysis confirmed the overall DAS-based injection profile. The comparison with the PLT injection allocation highlighted clear differences in the profiles. These are being discussed, as well as the possible causes for the discrepancies. This analysis demonstrates the strength of an integrated DAS and DTS analysis workflow using both transient and steady state conditions. DAS array processing techniques enabled the extraction of high-definition transient thermal plumes, allowing for an early injection profile, which was further strengthened by high SNR spectral noise logging.

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First Real-Time Fiber Optic Surveillance and Analysis of a Bullhead Stimulation of an Extended-Reach Horizontal Lateral in a Giant Offshore Carbonate Oil Field

Cited by 3 publications

References 3 publications

Injection Profiling Through Temperature Warmback Analysis Under Variable Injection Rate and Variable Injection Temperature

Injection Profiling Through Temperature Warmback Analysis Under Variable Injection Rate and Variable Injection Temperature

Injection Profiling for Intelligently Completed Wells Equipped with Fiber Optics

Advances in an Integrated Analysis Workflow of Distributed Acoustic Sensing and Distributed Temperature Sensing for Water Injection Profiling on a Horizontal Well

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