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Article

Flow Profiling Analysis of a Refractured Tight Oil Well Using Distributed Temperature Sensing

by
Changhao Yan
1,2,
Jiawei Ren
1,2,
Qiong Shi
3,
Xiangping Li
1,2,
Yuen Bai
1,2 and
Wei Yu
4,*
1
Oil & Gas Technology Research Institute, PetroChina Changqing Oilfield Company, Xi’an 710018, China
2
National Engineering Laboratory of Low Permeability Oil and Gas Field Exploration and Development, Xi’an 710018, China
3
Changqing Downhole Service Company, CNPC Chuanqing Drilling Engineering Company Limited, Xi’an 710018, China
4
SimTech LLC, Houston, TX 77494, USA
*
Author to whom correspondence should be addressed.
Processes 2024, 12(10), 2106; https://doi.org/10.3390/pr12102106
Submission received: 10 August 2024 / Revised: 24 September 2024 / Accepted: 25 September 2024 / Published: 27 September 2024
(This article belongs to the Special Issue Multiphase Flow, and Efficient Development Methodology and Technology in Unconventional Reservoirs (2nd Edition))
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Abstract

:
This study presents an in-depth analysis of a refractured tight oil well, focusing on both the initial and subsequent refracturing operations. After refracturing, daily oil production surged from 0.8 to 15.0 tons. The well sustained natural flow for 100 days before transitioning to pump-assisted production, resulting in an additional cumulative oil production of 1412 tons. Leveraging distributed temperature sensing (DTS), high-resolution temperature monitoring was performed, revealing key insights into the behavior of both newly created and existing fractures. Older perforation stages outperformed newer ones, with average daily oil production of 4.66 m3 for older stages and 3.49 m3 for newer stages under a 2 mm choke size. Moreover, CO2 pre-fracturing significantly enhanced oil production, with the stages receiving CO2 injection achieving a median daily oil output of 4.04 m3, compared to 3.55 m3 for non-CO2 stages. These results demonstrate the effectiveness of integrating advanced monitoring techniques and innovative fracturing methods to optimize refracturing strategies, ultimately enhancing hydrocarbon recovery in tight oil reservoirs.

1. Introduction

Refracturing in tight oil reservoirs has emerged as an essential strategy for enhancing hydrocarbon recovery and prolonging the productive life of existing wells. Initial hydraulic fracturing often fails to fully access all the available resources within the reservoir, leaving behind substantial untapped hydrocarbons [1]. Refracturing reopens these initial fractures and creates new pathways, significantly improving the overall permeability of the formation [2]. This process maximizes oil and gas extraction, offering a cost-effective alternative to drilling new wells. By leveraging existing infrastructure, refracturing not only reduces environmental impact but also minimizes operational costs, making it a crucial component in optimizing resource management and sustaining energy supply from mature shale plays [3].
Globally, there has been an increasing focus on enhancing refracturing techniques to improve recovery rates in unconventional reservoirs. Studies from major shale plays in the United States, such as Barnett, Bakken, Eagle Ford, and Permian Basin, have demonstrated substantial improvements in well performance following refracturing operations [4,5,6,7]. For instance, Indras and Blankenship [5] reported significant production increases in the Bakken Formation after refracturing treatments. Similar successes have been reported in China’s Changqing and Daqing oilfields, where refracturing practices have yielded notable enhancements in well productivity [8,9]. Studies from countries such as Saudi Arabia have also highlighted the potential of refracturing as an effective technique for boosting production in gas wells, demonstrating its ability to revitalize well performance and unlock additional reserves in mature reservoirs [10]. In Russia, refracturing has been employed to stimulate tight reservoirs, resulting in improved extraction rates [11,12]. Additionally, refracturing initiatives in Canada have also shown promising results, indicating the global applicability of these techniques [13,14,15]. These global advancements underscore the potential of refracturing as a viable method for rejuvenating mature wells and maximizing resource extraction.
Over the past decade, there has been a growing body of research focused on enhancing refracturing techniques to improve recovery rates in unconventional reservoirs [16,17,18,19,20,21,22]. Studies have demonstrated that refracturing can revitalize declining wells, increase production rates, and extend the economic life of assets [23]. However, the success of refracturing operations is highly variable and depends on factors such as reservoir characteristics, initial completion design, and the refracturing technique employed [24,25,26]. Advanced simulation models and diagnostic tools have been developed to better predict refracturing outcomes [21,27], yet challenges remain in understanding the complex interactions between new and existing fractures.
Monitoring the behavior of both new and old fractures after refracturing is critical to ensuring the success and efficiency of the operation [21,28]. Advanced monitoring techniques, such as microseismic monitoring, pressure mapping, and fiber-optic sensing, provide operators with real-time insights into fracture behavior and proppant distribution [29]. These data are invaluable for optimizing fracturing parameters and ensuring that new fractures effectively connect with the existing network to enhance hydrocarbon flow [30]. Despite extensive research on refracturing, there has been limited focus on monitoring production profiling per stage after refracturing, which is essential for evaluating the effectiveness of each fracturing stage and optimizing future operations.
The application of distributed temperature sensing (DTS) for flow profiling in unconventional oil and gas reservoirs has gained considerable attention in the industry [31]. DTS is a powerful tool for providing detailed insights into fluid dynamics and fracture performance within a wellbore. Utilizing fiber-optic cables, DTS measures temperature along the length of a wellbore in real time, operating on the principle of Raman scattering, where temperature variations are detected through changes in backscattered light signals [32]. Studies have demonstrated DTS’s capability in detecting temperature changes corresponding to fluid flow in shale wells, emphasizing its value when integrated with other logging tools to enhance the understanding of fracture effectiveness and fluid distribution [33]. Recent advancements have further refined DTS data interpretation, allowing for more accurate flow profiling, particularly in multi-stage fractured horizontal wells where fluid distribution is complex and heterogeneous. Despite significant progress, most DTS studies have focused on initial fracturing in shale reservoirs [34,35,36,37,38,39], with little attention given to its application in monitoring refractured wells.
CO2 pre-fracturing technology represents a promising approach to improving the efficiency of hydraulic fracturing operations while reducing their environmental impact [40]. This technology involves the initial injection of supercritical CO2, followed by slickwater to stimulate the reservoir. The process takes advantage of CO2’s unique physical and chemical properties, offering several benefits, such as increased formation energy, enhanced miscibility with oil, faster flowback, reduced formation damage, and the ability to generate more complex fracture networks [41,42,43,44,45]. Previous research has explored the mechanisms by which CO2 fracturing can enhance oil recovery, yet its application in field refracturing processes has not been extensively reported or investigated.
In this study, we conducted a comprehensive analysis of a refractured tight oil well in the ChangQing oil field, focusing on both the initial and subsequent refracturing designs and operations. By employing DTS for real-time temperature monitoring and advanced data interpretation techniques, we evaluated the impact of both new and existing fractures on well productivity. Additionally, we assessed the effectiveness of CO2 pre-fracturing technology in enhancing fracture networks and boosting hydrocarbon flow. This detailed evaluation provides valuable insights into optimizing refracturing strategies, ultimately improving the efficiency of hydrocarbon extraction in tight oil reservoirs. The findings contribute to the existing body of knowledge by highlighting the benefits of integrating advanced monitoring techniques with innovative refracturing methods.

2. Methodology

Distributed temperature sensing (DTS) is an advanced method used for production profiling in tight reservoirs, providing continuous temperature measurements along the length of a wellbore. By utilizing fiber-optic cables installed within the well, DTS offers real-time temperature data with high spatial resolution, typically on the order of meters, as illustrated in Figure 1. This technique is particularly beneficial in complex and heterogeneous tight reservoirs where traditional logging tools may struggle to provide accurate readings due to the variability in formation properties.
The underlying principle of DTS is based on Raman scattering, where an optical fiber acts as a linear sensor. When a laser pulse is transmitted through the fiber, it interacts with the molecular structure of the fiber, causing scattering. This scattered light consists of two components: Stokes and anti-Stokes signals, both of which are temperature dependent. By analyzing the ratio of these signals, the system can accurately determine the temperature at various points along the fiber. This capability makes DTS a powerful tool for monitoring downhole conditions and providing detailed insights into wellbore dynamics.
In the context of production profiling, the temperature data collected via DTS can reveal critical information about fluid flow within the wellbore. Variations in temperature along the well can indicate zones of fluid entry or exit, estimate flow rates, and assess the effectiveness of fracturing stages. By integrating DTS data with other reservoir and production information, operators can create a comprehensive production profile, optimize completion strategies, improve hydrocarbon recovery, and more effectively manage reservoir performance.
When liquid is produced downhole, it moves from the high-pressure formation into the lower-pressure wellbore, an exothermic process that results in a localized temperature increase. Theoretically, the greater the amount of liquid produced at a given point, the more significant the temperature increase. Conversely, when gas is produced, it transitions from the high-pressure formation to the low-pressure wellbore through an endothermic process involving heat absorption and volume expansion, leading to a localized temperature decrease. The greater the gas production, the more pronounced the temperature drop at that point.
To conduct a flow allocation analysis, DTS data are combined with downhole pressure data and surface flow rates. A rate computation thermal model based on the temperature survey is used to determine the flow rate distribution, as shown in Equation (1). This model simulates the pressure–temperature relationship within the wellbore and near-wellbore regions, applying error minimization techniques to match field DTS and downhole pressure data with the flow rate and the Joule–Thomson effect, as shown in Equation (2), across both depth and time domains. At each time step, the simulator uses geothermal temperature, individual cluster flow rates, and sandface fluid temperature, accounting for the Joule–Thomson effect, to calculate the temperature profile from the bottom of the well to the wellhead. The averaged thermal properties of production fluids are calculated using mass-weighted mixing rules in most cases. For more details on the thermal model validation and its application, refer to the work by Johnson et al. [46].
∂ 2 T ∂ r 2 + 1 p ∂ T ∂ r = ρ e c e k e ∂ T ∂ t
J T C =   ∂ T ∂ p H
where T is temperature, p is pressure, t is time, r is the radius of wellbore, ρe is effective density, ce is effective compressibility, ke is effective reservoir permeability, and JTC is the Joule–Thomson effect.
This integrated approach enables a more accurate and detailed understanding of wellbore dynamics, providing operators with the insights necessary to optimize production strategies and improve overall reservoir management.

3. Field Application

3.1. Initial Fracturing Design

Completed in 2012, the well reaches a total depth of 3660 m with a horizontal section extending 1415 m. The initial fracturing operation was carried out in May 2013, comprising 13 stages and 26 clusters, with an average stage spacing of 104 m. During this process, a total of 440 cubic meters of proppant was injected at a pumping rate of 4.0 cubic meters per minute, along with 3172 cubic meters of fluid. On average, each stage received 33.8 cubic meters of proppant and consumed 244 cubic meters of fracturing fluid, as detailed in Table 1.
Over the course of 10 years, the well has produced a cumulative total of 20892 cubic meters of fluid and 7334 tons of oil. However, before undergoing refracturing, the well’s daily production had declined to 2.2 cubic meters of fluid and 0.8 tons of oil, with a water cut of 55.7%.
The initial fracturing operation was relatively modest, with a limited number of stages and a smaller-scale intervention, which likely left residual oil between the stages. This underutilization of the reservoir suggests there is considerable potential for boosting production through a refracturing operation. Refracturing could effectively target these unstimulated areas, increasing the well’s productivity and extending its economic life.

3.2. Refracturing Design

The initial fracturing design was focused on establishing baseline production with a limited number of stages and clusters, reflecting a more conservative approach aimed at balancing stimulation effectiveness with operational costs and risks. The primary goal was to create sufficient fractures to stimulate production, but the design prioritized minimizing initial expenditures and operational uncertainties. In contrast, the refracturing design adopted a more targeted and aggressive strategy, incorporating lessons learned from the initial operation. This approach not only increased the number of stages and clusters but also integrated advanced techniques such as CO2 injection to enhance fracture conductivity and overall reservoir contact, thereby maximizing production potential.
The refracturing design specifically addressed the shortcomings identified in the initial fracturing process, such as insufficient fracture propagation in certain stages. By repressurizing these inadequately fractured stages and introducing new fractures in previously untreated zones, the refracturing aimed to optimize the extraction of hydrocarbons. This strategy was informed by a more detailed understanding of the reservoir’s geomechanics and the application of modern techniques, resulting in a more refined and effective fracturing process.
To ensure the refracturing process was as effective as possible, the original fracturing curves from each stage of the initial operation were meticulously collected and analyzed. This analysis focused on identifying significant fracturing pressures at each stage, which served as key indicators of the initial fracturing’s adequacy. Through this detailed examination, specific stages—namely, stages 2, 4, 12, 13, 16, 18, and 19—were identified as having insufficient initial fracturing. These stages were designated for the refracturing of old fractures, while the remaining stages were targeted for the creation of new fractures. This strategic approach was designed to optimize the contribution of both new and old fractures to the well’s overall production following refracturing.
To further enhance the sustained production capacity of these horizontal wells, a CO2-refrac experiment was implemented. This experiment utilized a comparative design, where 200 cubic meters of liquid CO2 was injected during the pre-pad stage of even-numbered stages, while odd-numbered stages did not receive CO2 injection. The objective was to quantitatively assess the impact of CO2 injection on fracturing performance and determine its potential to improve the effectiveness of the refracturing process. The casing-in-casing refracturing treatment method [47] was employed to ensure successful CO2 injection and effective sequestration, involving the insertion of a 4 1/2-inch casing into the existing 5 1/2-inch wellbore, followed by a secondary cementing operation to restore wellbore integrity.
In 2023, this methodical and innovative refracturing operation was successfully completed across 20 stages and 59 clusters. The operation included the re-pressurization of old fractures in 7 stages and the creation of new fractures in 13 stages. A total of 3380 cubic meters of proppant was injected, with 37,900 cubic meters of fluid pumped into the formation. Among these, 10 stages received a combined 2000 cubic meters of CO2 injection, as detailed in Table 2. Figure 2 provides a detailed comparison between the initial fracturing design and the subsequent refracturing design, highlighting key differences in approach, scale, and strategy. This comparison offers valuable insights into how refracturing can be optimized to enhance well productivity. The success of this approach underscores the importance of integrating advanced techniques and thorough analysis in enhancing well productivity and ensuring the long-term viability of tight oil operations.
Figure 3 demonstrates a substantial enhancement in daily oil production following the refracturing operation, with a significant increase from 0.8 to 15.0 tons per day. The well sustained this elevated production through natural flow for 100 days before transitioning to pump-assisted production, which is particularly highlighted in the last portion of the figure. This transition indicates that while natural reservoir pressure was sufficient initially, maintaining high production rates over time required supplemental lift, showcasing the effective management of reservoir energy. To date, this strategic shift has resulted in an additional cumulative oil production of 1412 tons, emphasizing a remarkable improvement in well performance. The sustained high output not only confirms the success of the refracturing in revitalizing the well but also underscores its significant impact on enhancing production capacity over an extended period. This outcome highlights the potential of refracturing combined with optimized production strategies to significantly increase output in mature wells, offering valuable insights for similar enhancement operations in other fields.

3.3. DTS Measurements

After refracturing, the well was flowed back for 7 days to stabilize oil and water production. Following this stabilization period, DTS data were collected using fiber optic coiled tubing. The fiber optic monitoring system, as shown in Figure 4, employed a 4 mm fiber optic cable pre-installed within a 2-inch coiled tubing. This monitoring operation covered 20 stages along the wellbore. The fiber optic system offered a high spatial resolution of 1.0 m and a sampling resolution of 0.498 m, with temperature measurement accuracy within 0.5 °C and a fine temperature resolution of 0.01 °C. The temperature data were sampled every 60 s, and on-site calibration was conducted using dual-laser monitoring equipment to ensure data precision.
Temperature measurements were taken for 12, 4, 4, 12, 35, and 12 h, corresponding to choke sizes of 0, 5, 4, 2, 0, and 4 mm, respectively, as detailed in Table 3 and Figure 5. However, due to excessive flowback volumes, the DTS data collected under the 5 and 4 mm choke sizes were deemed unreliable and were excluded from the analysis. Instead, the DTS data collected before and after well shut-in with the final 2 and 4 mm choke sizes were selected for detailed analysis.
This comprehensive analysis involved correlating the temperature monitoring data with the corresponding wellhead pressure and liquid production data, as illustrated in Figure 6. By examining these datasets, we were able to analyze and summarize the contribution of each cluster to oil and water production. The insights derived from this analysis provide valuable data support and recommendations for optimizing future fracturing operations in this field. This approach not only enhances the understanding of well performance but also informs the development of more effective production strategies in similar reservoirs.
Figure 7 presents a comparison of the measured temperature curves for two different choke sizes against the geothermal baseline. This comparison reveals that the production regime utilizing the 4 mm choke size yields a higher liquid production rate than the 2 mm choke size. The temperature curves show a notable deviation from the geothermal baseline, particularly in the 2200 to 2900 m section of the well. This significant temperature difference indicates that this section is contributing substantially to the overall liquid production.
The analysis underscores the critical role of temperature monitoring in understanding well performance. Variations in temperature along the wellbore provide valuable insights into the specific intervals that are most productive. This information is crucial for identifying zones with higher hydrocarbon flow and optimizing production strategies.
The findings suggest that by fine-tuning choke size and production parameters based on detailed temperature data, operators can significantly enhance overall well productivity. This approach not only improves current operations but also provides a framework for optimizing future well management and fracturing designs in similar reservoirs. By leveraging such precise temperature monitoring, operators can make more informed decisions, leading to improved recovery rates and more efficient resource management.

3.4. DTS Interpretation

During the development of the DTS interpretation model, a range of critical parameters were incorporated, including the well depth structure, wellbore trajectory, temperature curves, perforation data, wellhead production rates, and wellhead pressure drops. With these inputs established, the model utilized production properties and pressure drop matching as baseline values to initiate the simulation of production zones. The initial random assignment and simulation provided a foundational understanding of the well’s behavior under different operational conditions.
The model subsequently generated a simulated temperature curve, which was then compared against the actual DTS data. In cases where significant discrepancies were observed between the simulated and measured curves, the model’s initial parameters were adjusted. This iterative process involved multiple rounds of simulation and comparison, refining the model’s accuracy with each iteration. The process continued until the error between the simulated and measured curves fell within acceptable quality control standards, at which point the model was considered complete.
This iterative approach is essential for enhancing the precision of the DTS interpretation model. By continuously refining the model based on real-world data, it becomes more adept at accurately representing the actual production conditions within the well. This method ensures that the final model is not only robust but also reliable, serving as a solid foundation for further analysis, well management, and optimization decisions.
Figure 8 and Figure 9 present the comparisons between the simulated and measured DTS curves for choke sizes of 2 and 4 mm, respectively. The strong correlation between the simulated and actual values highlights the model’s reliability in accurately capturing the production profile of each stage in this refractured tight oil well. This close alignment not only validates the model but also demonstrates its effectiveness in providing valuable insights into the well’s performance, enabling more informed and strategic operational decisions. Further analysis of oil and water flow rates per stage and cluster for the 2 and 4 mm choke sizes is depicted in Figure 10 and Figure 11, respectively, offering a detailed view of the production dynamics under varying operational conditions.
Figure 12 and Figure 13 illustrate the comparison of oil and water production across different stages under varying choke sizes based on DTS interpretation. The data show that the oil and water production profiles are consistent between the 2 and 4 mm choke sizes, with the primary production contributions coming from the middle to heel sections of the horizontal well.
It is inferred that the well is still in the early stages of flowback, where the middle and heel sections of the well are easier to flow back, potentially suppressing flowback from the toe section. This results in most of the oil and water production being concentrated in the middle and heel segments of the horizontal section. The testing results indicate that each perforated stage along the horizontal section contributes to fluid production.
Under both operational regimes, the 10 stages from the middle to the heel are identified as the main oil and water-producing zones for this well. Notably, increasing the choke size does not seem to engage additional fractured stages. In both production scenarios, oil and water are produced concurrently, and the total fluid production does not show a significant correlation with the volume of injected fluid, sand, or the number of perforation clusters in each stage. This analysis suggests that the production profile is more influenced by the well’s structural and flowback characteristics than by variations in choke size or stimulation intensity.

3.5. Comparison of Oil Production between Old and New Fractures

Figure 14 compares oil production between new and old stages under different choke sizes. The data show that under the 2 mm choke size, the average daily oil production for new stages is 3.49 m3, while for old stages, it is 4.66 m3. Under the 4 mm choke size, the average daily oil production increases slightly to 3.98 m3 for new stages and 4.69 m3 for old stages. The older stages, which are mostly located in the middle to heel sections of the horizontal well, generally outperform the new stages in terms of average production.
This finding is particularly significant for the well that was studied in this research, suggesting that older fractures may still contribute significantly to production even after refracturing. However, it is important to note that this conclusion cannot be universally applied to all horizontal wells. The production contribution of refractured old fractures compared to new ones may vary depending on several factors, including reservoir properties and well conditions. It should be emphasized that optimizing the fracture placement in refractured wells should be primarily based on reservoir “sweet spots”, as multiple factors can influence the productivity of a refractured well. These findings underscore the need for a tailored approach to refracturing, considering the unique characteristics of each well and its reservoir.

3.6. Comparison of Oil Production with and without CO2 Injection

Figure 15 compares oil production with and without CO2 injection under different choke sizes. The data show that under the 2 mm choke size, the median daily oil production for stages with CO2 injection is 4.04 m3, compared to 3.55 m3 for stages without CO2 injection. Similarly, under the 4 mm choke size, the median daily oil production for stages with CO2 injection is 4.065 m3, while it is 4.035 m3 for stages without CO2 injection. This indicates that stages with CO2 injection outperform those without CO2 injection in terms of oil production.
Laboratory experiments have demonstrated that CO2’s low viscosity and high diffusivity allow it to penetrate pores and microfractures, creating a localized pressurization effect that can reduce fracture initiation pressure and enhance fracture complexity [42]. Compared to conventional slickwater used as a pre-pad fluid, CO2 injection has shown better production enhancement results. The findings from the DTS fiber optic production profiling test in this study align with these laboratory results, confirming the beneficial impact of CO2 injection on oil production.
This study highlights the effectiveness of CO2 injection in improving oil recovery in refractured wells. The enhanced performance is attributed to CO2’s unique properties, which not only facilitate the propagation of complex fractures but also optimize the stimulation process. These insights could be valuable for future fracturing operations, suggesting that incorporating CO2 injection could be a strategic choice for maximizing production, especially in tight oil formations where traditional methods may be less effective.

4. Conclusions

This study employed distributed temperature sensing (DTS) via fiber optic coiled tubing to conduct an extensive temperature monitoring program across the entire wellbore of a refractured tight oil well. DTS data were collected with a spatial resolution of 1 m and a sampling resolution of 0.498 m, providing precise temperature measurements with an accuracy of ±0.5 °C and a temperature resolution of 0.01 °C. Temperature monitoring was conducted for a total of 79 h under different choke sizes to capture the well’s performance. The comprehensive analysis of DTS data enabled both qualitative and quantitative evaluations of production performance under two distinct operational regimes. Notably, daily oil production surged from 0.8 to 15.0 tons following the refracturing operation, and the well sustained this elevated production through natural flow for 100 days before transitioning to pump-assisted production, resulting in an additional cumulative oil production of 1412 tons. The results clearly indicate that every perforation stage along the horizontal section of the well contributed to fluid production, with the middle to heel sections, comprising 10 stages, emerging as the primary zones for oil and fluid production. Interestingly, increasing the choke size from 2 mm to 4 mm did not significantly activate additional fractured stages, suggesting that the well’s production is more influenced by the existing fracture network than by operational adjustments like choke size changes.
Furthermore, the study revealed that oil and water were produced concurrently across the well, with no significant correlation between oil production and variables such as the volume of injected fluid, the amount of proppant used, or the number of perforation clusters per stage. This finding underscores the complexity of production dynamics in tight reservoirs, where factors beyond the immediate fracturing parameters play a critical role in determining output.
The comparison of oil production between different stimulation methods provided additional insights. Notably, the older perforation stages outperformed the new ones in terms of average oil production, indicating that even after refracturing, older fractures can still contribute significantly to the well’s productivity. Specifically, under a 2 mm choke size, the older fractures produced an average daily oil output of 4.66 m3, while new fractures produced 3.49 m3. Similarly, under a 4 mm choke size, older fractures achieved 4.69 m3 compared to 3.98 m3 from new fractures. Moreover, stages that received CO2 injection demonstrated enhanced oil production compared to those that did not. Under a 2 mm choke size, CO2-injected stages achieved a median daily oil output of 4.04 m3, compared to 3.55 m3 in non-CO2 stages. Similarly, at a 4 mm choke size, CO2-injected stages produced 4.065 m3 daily versus 4.035 m3 in non-CO2 stages. These results highlight the potential of CO2-refrac as an effective method for boosting hydrocarbon recovery.
These findings offer a solid data foundation for optimizing refracturing strategies and analyzing production enhancement effects. The CO2-refrac method, in particular, demonstrated significant potential for improving production outcomes in mature wells. This study contributes valuable knowledge to the field, suggesting that CO2 injection could play a pivotal role in future refracturing operations. To build on these findings, future research should integrate physical simulation experiments and advanced numerical modeling to further explore the underlying mechanisms driving these production enhancements. This would not only deepen the understanding of fracture behavior and fluid flow in tight reservoirs but also guide the development of more effective and efficient refracturing strategies, ultimately leading to more sustainable hydrocarbon extraction practices.

Author Contributions

Conceptualization, C.Y.; methodology, J.R.; writing—original draft preparation, C.Y.; writing—review and editing, Q.S.; visualization, X.L. and Y.B.; supervision W.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the CNPC Changqing Oilfield Company technology project (2024D4GY35) and the CNPC major science and technology project (Grant No. 2023ZZ17YJ03, 2023ZZ28YJ07).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

Author Changhao Yan, Jiawei Ren, Xiangping Li, Yuen Bai were employed by the company PetroChina Changqing Oilfield Company. Author Qiong Shi was employed by the company Changqing Downhole Service Company, CNPC Chuanqing Drilling Engineering Company Limited. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Economides, M.J.; Nolte, K.G. Reservoir Stimulation, 3rd ed.; Wiley: Chichester, UK, 2000. [Google Scholar]
  2. Shah, M.; Shah, S.; Sircar, A. A Comprehensive Overview on Recent Developments in Refracturing Technique For Shale Gas Reservoirs. J. Nat. Gas Sci. Eng. 2017, 46, 350–364. [Google Scholar] [CrossRef]
  3. Melcher, J.; Persac, S.; Whitsett, A. Restimulation Design Considerations and Case Studies of Haynesville Shale. In Paper SPE 174819, Proceedings of the SPE Annual Technical Conference and Exhibition, Houston, TX, USA, 28–30 September 2015; SPE: Houston, TX, USA, 2015. [Google Scholar]
  4. Tavassoli, S.; Yu, W.; Javadpour, F.; Sepehrnoori, K. Selection of Candidate Horizontal Wells and Determination of the Optimal Time of Refracturing in Barnett Shale (Johnson County). In Paper SPE 167137, Proceedings of the SPE Unconventional Resources Conference-Canada, Calgary, AB, Canada, 5–7 November 2013; SPE: Calgary, AB, Canada, 2013. [Google Scholar]
  5. Indras, P.; Blankenship, C. A Commercial Evaluation of Refracturing Horizontal Shale Wells. In Paper SPE 174951, Proceedings of the SPE Annual Technical Conference and Exhibition, Houston, TX, USA, 28–30 September 2015; SPE: Houston, TX, USA, 2015. [Google Scholar]
  6. Garza, M.; Baumbach, J.; Prosser, J.; Pettigrew, S.; Elvig, K. An Eagle Ford Case Study: Improving an Infill Well Completion Through Optimized Refracturing Treatment of the Offset Parent Wells. In Paper SPE194374, Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, USA, 5–7 February 2019; SPE: The Woodlands, TX, USA, 2019. [Google Scholar]
  7. Quirein, J.A.; Kessler, C.; Trela, J.M.; Zannoni, S.; Cornish, B.; Brewer, R.J.; Gordy, D.; Pettitt, W.S.; Walker, C.B.; Laney, J.; et al. Microseismic Monitoring of a Restimulation Treatment to a Permian Basin San Andres Dolomite Horizontal Well. In Paper SPE 110333, Proceedings of the SPE Annual Technical Conference and Exhibition, Anaheim, CA, USA, 11–14 November 2007; SPE: Anaheim, CA, USA, 2007. [Google Scholar]
  8. Ren, J.; Chen, J.; Lu, H.; Bai, X.; Yu, W. Optimizing Refracturing Models in Tight Oil Reservoirs: An Integrated Workflow of Geology and Engineering Based on Seepage-Stress Real-Time Cross-Coupling Strategy. SPE J. 2024, 1–13. [Google Scholar] [CrossRef]
  9. Wang, X.; Wang, W.; Li, B.; Li, D.; Gu, M.; Tang, P.; Zhang, H.; Liu, Y.; Li, Y.; Wang, J. The Application of Refracturing Technique in Horizontal Wells of Daqing Oilfield. In Paper SPE 192787, Proceedings of the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, United Arab Emirates, 12–15 November 2018; SPE: Abu Dhabi, United Arab Emirates, 2018. [Google Scholar]
  10. Rahim, Z.; Al-Anazi, H.; Waspada, D.; Al-Kanaan, A. Comprehensive Reservoir Assessment and Refracturing Improve Saudi Arabian Gas Well Deliverability. In Paper SPE 164453, Proceedings of the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 10–13 March 2013; SPE: Manama, Bahrain, 2013. [Google Scholar]
  11. Borisenko, A.; Parkhonyuk, S.; Zotov, K.; Korkin, R.; Kiselev, N.V.; Laptev, A.; Rapeyko, V.T. Advanced Pressure Monitoring Technique—New Horizons of Workover in Russia. In Paper SPE 202070, Proceedings of the SPE Russian Petroleum Technology Conference, Moscow, Russia, 12–14 October 2020; SPE: Moscow, Russia, 2020. [Google Scholar]
  12. Valiullin, A.; Makienko, V.; Yudin, A.; Overin, A.; Gromovenko, A. Channel Fracturing Technique Helps to Revitalize Brown Fields in Langepas Area. In Paper SPE 178131, Proceedings of the SPE Oil and Gas India Conference and Exhibition, Mumbai, India, 24–26 November 2015; SPE: Mumbai, India, 2015. [Google Scholar]
  13. Urban-Rascon, E.; Virues, C.; Aguilera, R. 3D Geomechanical Modeling in the Complex Fracture Network of the Horn River Shale Using a Fully-Coupled Hybrid Hydraulic Fracture HHF Model: Permeability Evolution and Depletion. In Paper SPE 189795, Proceedings of the SPE Canada Unconventional Resources Conference, Calgary, AB, Canada, 13–14 March 2018; SPE: Calgary, AB, Canada, 2018. [Google Scholar]
  14. Hlidek, B.; MacDonald, D.; Gee, C.; Makowecki, B. Slimhole Refracturing Case Studies and Experience Utilizing Mechanical Isolation for Effective Refracture Treatments. In Paper SPE 180236, Proceedings of the SPE Low Perm Symposium, Denver, CO, USA, 5–6 May 2016; SPE: Denver, CO, USA, 2016. [Google Scholar]
  15. Urban-Rascon, E.; Aguilera, R. Hydraulic Fracturing Modeling, Fracture Network, and Microseismic Monitoring. In Paper SPE 199976, Proceedings of the SPE Canada Unconventional Resources Conference, Calgary, AB, Canada, 18–19 March 2020; SPE: Calgary, AB, Canada, 2020. [Google Scholar]
  16. Kurison, C. Impediments to Refracturing Success in Shale Reservoirs. In Paper SPE 204799, Proceedings of the SPE Middle East Oil & Gas Show and Conference, Manama, Bahrain, 28 November–1 December 2021; SPE: Manama, Bahrain, 2021. [Google Scholar]
  17. Dalkhaa, C.; Azzolina, N.A.; Chakhmakhchev, A.; Kurz, B.A.; Sorensen, J.A.; Gorecki, C.D.; Harju, J.A. Refracturing in the Bakken—An Analysis of Data from Across North Dakota. In Paper URTeC 3723732, Proceedings of the Unconventional Resources Technology Conference, Houston, TX, USA, 20–22 June 2022; URTeC: Houston, TX, USA, 2022. [Google Scholar]
  18. Bryan, E.; Richard, R.; Holasek, C.; Hosseinpour-Zonoozi, N.; Ilk, D.; Melvin, C.; Eichinger, K.; Rankosky, B.; Ingalls, B.; French, S.; et al. Integrated Well Performance Analysis Methodology to Understand Production Performance and Identify Refracturing Candidates in Barnett Shale. In Paper URTeC 3869654, Proceedings of the Unconventional Resources Technology Conference, Denver, CO, USA, 13–15 June 2023; URTeC: Denver, CO, USA, 2023. [Google Scholar]
  19. Barba, R.; Villarreal, M. The Economics of Refracturing in the Haynesville. In Paper SPE 212371, Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, USA, 31 January–2 February 2023; SPE: The Woodlands, TX, USA, 2023. [Google Scholar]
  20. Brinkley, K.; Thompson, C.; Haffener, J.; White, S.; Ketter, C.; Borell, J.; Comisky, J.; Hart, E.; Haustveit, K.; Herrin, M.; et al. Redefining Recoverable Reserves in the Eagle Ford: Refracs and InfillDevelopment Lessons Learned from the Hydraulic Fracturing Test Site 1(HFTS) Phase 3. In Paper SPE 212340, Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, USA, 31 January–2 February 2023; SPE: The Woodlands, TX, USA, 2023. [Google Scholar]
  21. Pehlke, T.; Simpson, G.; Maxwell, T.; Bourgeois, C.; Stibbs, J.; Littleford, T. On Track for Refrac: Targeting Under-Stimulated Stages and Assessing Casing Integrity Defects with High-Resolution Acoustic Imaging. In Paper SPE 217768, Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, USA, 6–8 February 2024; SPE: The Woodlands, TX, USA, 2024. [Google Scholar]
  22. Goodwin, A.; Nguyen, A. Where Are Refracs Going, and Can We Make Them a Sure Thing? J. Pet. Technol. 2024, 76, 10–12. [Google Scholar]
  23. Asala, H.I.; Ahmadi, M.; Taleghani, A.D. Why Re-Fracturing Works and Under What Conditions. In Paper SPE181516, Proceedings of the SPE Annual Technical Conference and Exhibition, Dubai, United Arab Emirates, 26–28 September 2016; SPE: Dubai, United Arab Emirates, 2016. [Google Scholar]
  24. Kiselica, K.; Jennings, T. Re-Fracturing the Appalachian Basin: An Economic Analysis. In Paper SPE 196602, Proceedings of the SPE Eastern Regional Meeting, Charleston, WV, USA, 15–17 October 2019; SPE: Charleston, WV, USA, 2019. [Google Scholar]
  25. Jie, B.; Leopoldo, S.; Vladimir, M. Recompletion with Consideration of Depletion Effect in Naturally Fractured Unconventional Reservoirs. In Paper ARMA 19–321, Proceedings of the 53rd US Rock Mechanics/Geomechanics Symposium, New York, NY, USA, 23–26 June 2019; ARMA: New York, NY, USA, 2019. [Google Scholar]
  26. Janiczek, P.; Makar, I.; Reilly, B.; Lahman, M.; Kolasa, B.; Day, R. Selecting a Horizontal Well Candidate in the Black Sea for Refracturing with Flow Diverting Technology. In Paper SPE 190839, Proceedings of the 80th EAGE Conference and Exhibition, Copenhagen, Denmark, 11–14 June 2018; SPE: Copenhagen, Denmark, 2018. [Google Scholar]
  27. Rassenfoss, S. Who’s Right? Imaging of Fractures Often Delivers Conflicting Measures. J. Pet. Technol. 2023, 75, 22–28. [Google Scholar] [CrossRef]
  28. Fayzullin, M.; Janiczek, P.; Contreras, D.; Makar, I.; Gonzalez, J.; Day, R. Redevelopment of an Unconventional Oil Reservoir: Finding Unstimulated and Bypassed Reservoir Volume. In Paper SPE 188647, Proceedings of the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, United Arab Emirates, 13–16 November 2017; SPE: Abu Dhabi, United Arab Emirates, 2017. [Google Scholar]
  29. Wu, K.; Liu, Y.; Jin, G.; Srinivasan, A. Hydraulic Fracture Geometry Characterization based on Distributed Fiber Optic Strain Measurements; Elsevier: Cambridge, MA, USA, 2024; ISBN 9780323953627. [Google Scholar]
  30. Wu, K.; Liu, Y.; Jin, G.; Moridis, G. Fracture hits and hydraulic-fracture geometry characterization using low-frequency distributed acoustic sensing strain data. J. Pet. Technol. 2021, 73, 39–42. [Google Scholar] [CrossRef]
  31. Dawson, P.; Jimenez, E.; Mahue, V.; Kitchen, J.; Mehrok, M.; Zinselmeyer, R.; Wygal, B.; Chuckry, T. Repeat DAS and DTS Logging for Production and Cluster Efficiency Evaluation on a Gas Condensate Producer in the Montney Formation. In Papper URTeC 4054931, Proceedings of the Unconventional Resources Technology Conference, Houston, TX, USA, 17–19 June 2024; URTeC: Houston, TX, USA, 2024. [Google Scholar]
  32. Lu, C.; Chen, Y.; Wang, Z. Principles and Applications of Distributed Temperature Sensing in Oil and Gas Industry. Pet. Sci. 2016, 13, 345–357. [Google Scholar]
  33. Brown, K.; Smith, J.; Johnson, L. Application of Distributed Temperature Sensing in Barnett Shale. J. Pet. Technol. 2012, 64, 92–99. [Google Scholar]
  34. Kabir, C.S.; Izgec, B.; Hasan, A.R.; Wang, X.; Lee, J. Real-Time Estimation of Total Flow Rate and Flow Profiling in DTS-Instrumented Wells. In Paper IPTC 12343, Proceedings of the International Petroleum Technology Conference, Kuala Lumpur, Malaysia, 3–5 December 2008; IPTC: Kuala Lumpur, Malaysia, 2008. [Google Scholar]
  35. Guo, Y.; Li, H.; Zhang, X. Integrated Model for DTS Data Interpretation in Shale Reservoirs. Energy Fuels 2018, 32, 4321–4334. [Google Scholar]
  36. Sun, H.; Yu, W.; Sepehrnoori, K. Integrated Fracture Characterization and Flow Profiling with Distributed Temperature Sensing. In Paper SPE 201619, Proceedings of the SPE Annual Technical Conference & Exhibition, Denver, CO, USA, 5–7 October 2020; SPE: Denver, CO, USA, 2020. [Google Scholar]
  37. Luo, H.; Li, Y.; Li, H.; Cui, X.; Chen, Z. Simulated Annealing Algorithm-Based Inversion Model to Interpret Flow Rate Profiles and Fracture Parameters for Horizontal Wells in Unconventional Gas Reservoirs. SPE J. 2021, 26, 1679–1699. [Google Scholar] [CrossRef]
  38. Liu, C.; Yang, X.; Chang, C.; Liu, S.; Li, N.; Yu, W.; Sepehrnoori, K. A Novel Workflow to Characterize Production Profiles of Shale Gas Horizontal Wells Using Distributed Temperature Sensing Data. In Paper URTeC 4044221, Proceedings of the Unconventional Resources Technology Conference, Houston, TX, USA, 17–19 June 2024; URTeC: Houston, TX, USA, 2024. [Google Scholar]
  39. Mao, Y.; Godefroy, C.; Gysen, A. Case Studies: Integrated Production Profiling Analyses from Distributed Temperature and Acoustic Data. In Paper URTeC 4027567, Proceedings of the Unconventional Resources Technology Conference, Houston, TX, USA, 17–19 June 2024; URTeC: Houston, TX, USA, 2024. [Google Scholar]
  40. Middleton, R.S.; Carey, J.W.; Currier, R.P.; Hyman, J.D.; Kang, Q.; Karra, S.; Jiménez-Martínez, J.; Porter, M.; Viswanathan, H. Shale Gas and Non-aqueous Fracturing Fluids: Opportunities and Challenges for Supercritical CO2. Appl. Energy 2015, 147, 500–509. [Google Scholar] [CrossRef]
  41. Li, L.; Su, Y.; Chen, Z.; Fan, L.; Tang, M.; Tu, J. Experimental Investigation on EOR and Flowback Rate of Using Supercritical CO2 as Pre-Fracturing Fluid in Tight Oil Reservoir. In Paper SPE 202279, Proceedings of the SPE Asia Pacific Oil & Gas Conference and Exhibition, Perth, Australia, 20–22 October 2020; SPE: Perth, Australia, 2020. [Google Scholar]
  42. Zou, Y.; Zhang, S.; Ma, X.; Li, S. Improving Fracture Complexity and Conductivity in Shale Formation with Calcite-Filled Natural Fractures by a Novel CO2-Assisted Fracturing: An Experimental Study. SPE J. 2022, 27, 2109–2125. [Google Scholar] [CrossRef]
  43. Sun, L.; Wang, H.; Wang, B.; Dang, K.; Shi, M.; Zhang, Y.; Liu, M.; Wu, Y. The Effect of SCCO2 Treatments on the Petrophysical Properties of Continental Shale with Different Mineral Compositions. In Paper ARMA 23–467, Proceedings of the 57th US Rock Mechanics/Geomechanics Symposium, Atlanta, GA, USA, 25–28 June 2023; ARMA: Atlanta, GA, USA, 2023. [Google Scholar]
  44. Han, X.; Song, Z.; Deng, S.; Li, B.; Li, P.; Zhang, L.; Song, Y. Experimental and Numerical Study on the Phase Behavior and Distribution Characteristics of Oil-CO2-Water Three-Phase Fluid During Pre-CO2 Energized Fracturing in Shale Reservoirs. In Paper IPTC 24393, Proceedings of the International Petroleum Technology Conference, Dhahran, Saudi Arabia, 12–14 February 2024; IPTC: Dhahran, Saudi Arabia, 2024. [Google Scholar]
  45. Tang, W.; Zhou, F.; Hu, L.; Huang, G.; Li, L. Permeability Variation During CO2 Pre-Fracturing in Shale Reservoir: A Case Study of Junggar Basin. In Paper URTeC 4035176, Proceedings of the Unconventional Resources Technology Conference, Houston, TX, USA, 17–19 June 2024; URTeC: Houston, TX, USA, 2024. [Google Scholar]
  46. Johnson, D.; Sierra, J.; Kaura, J.; Guatieri, D. Successful Flow Profiling of Gas Wells Using Distributed Temperature Sensing Data. In Paper SPE 103097, Proceedings of the SPE Annual Technical Conference and Exhibition, San Antonio, TX, USA, 24–27 September 2006; SPE: San Antonio, TX, USA, 2006. [Google Scholar]
  47. Cadotte, R.J.; Elbel, B.; Modeland, N. Unconventional Multiplay Evaluation of Casing-in-Casing Refracturing Treatments. In Paper SPE 191451, Proceedings of the SPE International Hydraulic Fracturing Technology Conference and Exhibition, Muscat, Oman, 16–18 October 2018; SPE: Muscat, Oman, 2018. [Google Scholar]
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Figure 1. Measurement of temperature profile using DTS.
Figure 1. Measurement of temperature profile using DTS.
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Figure 2. Comparison between the initial fracturing design and the subsequent refracturing design (different color represents different stages): (a) initial fracturing design; (b) refracturing design.
Figure 2. Comparison between the initial fracturing design and the subsequent refracturing design (different color represents different stages): (a) initial fracturing design; (b) refracturing design.
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Figure 3. Comparison of daily production rate before and after refracturing.
Figure 3. Comparison of daily production rate before and after refracturing.
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Figure 4. Field DTS measurement via coiled tubing: (a) on-site photos of DTS monitoring; (b) distributed fiber optic cable deployed through coiled tubing.
Figure 4. Field DTS measurement via coiled tubing: (a) on-site photos of DTS monitoring; (b) distributed fiber optic cable deployed through coiled tubing.
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Figure 5. Water fall plot of DTS measurement data.
Figure 5. Water fall plot of DTS measurement data.
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Figure 6. Surface pressure and liquid production during the DTS measurement period.
Figure 6. Surface pressure and liquid production during the DTS measurement period.
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Figure 7. Comparison of measured temperature curves for two different choke sizes against the geothermal baseline.
Figure 7. Comparison of measured temperature curves for two different choke sizes against the geothermal baseline.
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Figure 8. Comparison of simulated vs. measured DTS curves for a 2 mm choke size.
Figure 8. Comparison of simulated vs. measured DTS curves for a 2 mm choke size.
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Figure 9. Comparison of simulated vs. measured DTS curves for a 4 mm choke size.
Figure 9. Comparison of simulated vs. measured DTS curves for a 4 mm choke size.
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Figure 10. Interpretation of oil and water flow rates per stage and cluster for a 2 mm choke size.
Figure 10. Interpretation of oil and water flow rates per stage and cluster for a 2 mm choke size.
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Figure 11. Interpretation of oil and water flow rates per stage and cluster for a 4 mm choke size.
Figure 11. Interpretation of oil and water flow rates per stage and cluster for a 4 mm choke size.
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Figure 12. Comparison of oil production across stages under different choke sizes.
Figure 12. Comparison of oil production across stages under different choke sizes.
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Figure 13. Comparison of water production across stages under different choke sizes.
Figure 13. Comparison of water production across stages under different choke sizes.
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Figure 14. Comparison of oil production between new and old stages under different choke sizes: (a) 2 mm choke size; (b) 4 mm choke size.
Figure 14. Comparison of oil production between new and old stages under different choke sizes: (a) 2 mm choke size; (b) 4 mm choke size.
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Figure 15. Comparison of oil production with and without CO2 injection under different choke sizes: (a) 2 mm choke size; (b) 4 mm choke size.
Figure 15. Comparison of oil production with and without CO2 injection under different choke sizes: (a) 2 mm choke size; (b) 4 mm choke size.
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Table 1. Summary of basic completion information for the initial fracturing design.
Table 1. Summary of basic completion information for the initial fracturing design.
Stage NumberCluster Perforation Location (m)Sand Volume (m3)Fluid Volume (m3)
13576.7, 3591.835258.7
23484.0, 3499.130225.4
33391.9, 3407.025226.6
42891.9, 2907.025219.4
52820.3, 2835.430212.1
62737.3, 2752.435234.6
72654.6, 2669.735258.0
82564.7, 2579.835236.3
92478.6, 2493.640264.8
102386.9, 2402.435238.9
112297.8, 2313.240266.6
122229.2, 2244.735241.4
132147.4, 2162.940289.6
Table 2. Summary of basic completion information for refracturing design.
Table 2. Summary of basic completion information for refracturing design.
Stage NumberCluster Perforation Location (m)Sand Volume (m3) Fluid Volume (m3)New or Old StagesCO2 Injection Volume (m3)
13545.5, 3535.5, 3525.512.01600.0New Stage/
23503.0, 3492.0, 3479.012.01400.0Old Stage200
33456.0, 3446.0, 3432.012.01600.0New Stage/
43400.0, 3386.012.01300.0Old Stage200
53366.0, 3354.012.01500.0New Stage/
63284.0, 3274.012.01300.0New Stage200
73244.0, 3230.0, 3216.012.01600.0New Stage/
83170.0, 3160.0, 3150.012.01400.0New Stage200
93128.0, 3118.0, 3110.012.01600.0New Stage/
103085.0, 3074.0, 3060.012.01400.0New Stage200
113034.0, 3022.0, 3012.0, 3000.012.01700.0New Stage/
122899.0, 2886.0
2875.0, 2868.0		12.01591.0Old Stage200
132840.0, 2825.0
2815.0, 2805.0		12.01506.0Old Stage/
142782.0, 2768.0, 2757.012.01550.0New Stage200
152732.0, 2722.0, 2712.012.01600.0New Stage/
162686.0, 2675.0, 2660.0, 2650.012.01591.0Old Stage200
172626.0, 2616.0, 2604.012.01600.0New Stage/
182569.0, 2558.0, 2548.0, 2540.012.01591.0Old Stage200
192320.0, 2306.0, 2294.0, 2284.012.01591.0Old Stage/
202206.0, 2196.0, 2186.012.01600.0New Stage200
Table 3. Summary of DTS measurement time and the corresponding choke size.
Table 3. Summary of DTS measurement time and the corresponding choke size.
Choke Size (mm)DTS Measurement Time (h)Note
012Well temporarily shut-in
54The liquid flowback volume is excessive
44The liquid flowback volume is excessive
212/
035Well temporarily shut-in
412/
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Yan, C.; Ren, J.; Shi, Q.; Li, X.; Bai, Y.; Yu, W. Flow Profiling Analysis of a Refractured Tight Oil Well Using Distributed Temperature Sensing. Processes 2024, 12, 2106. https://doi.org/10.3390/pr12102106

AMA Style

Yan C, Ren J, Shi Q, Li X, Bai Y, Yu W. Flow Profiling Analysis of a Refractured Tight Oil Well Using Distributed Temperature Sensing. Processes. 2024; 12(10):2106. https://doi.org/10.3390/pr12102106

Chicago/Turabian Style

Yan, Changhao, Jiawei Ren, Qiong Shi, Xiangping Li, Yuen Bai, and Wei Yu. 2024. "Flow Profiling Analysis of a Refractured Tight Oil Well Using Distributed Temperature Sensing" Processes 12, no. 10: 2106. https://doi.org/10.3390/pr12102106

APA Style

Yan, C., Ren, J., Shi, Q., Li, X., Bai, Y., & Yu, W. (2024). Flow Profiling Analysis of a Refractured Tight Oil Well Using Distributed Temperature Sensing. Processes, 12(10), 2106. https://doi.org/10.3390/pr12102106

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