In order to extend the life cycle of the developed oilfield and ensure the stable production of the oilfield, the exploration and practice of supplementary energy refracturing has been carried out in a small block in eastern China which is on the verge of shutdown since 2017. All of the well in this block are vertical wells. This technology breaks the injection production relationship of the original well pattern. The injection wells and production wells are fractured at the same time. Fracturing fluid is not only used for fracturing, but also for supplementing formation energy. In order to produce more new fractures and make them more complex, low viscosity slippery water is used in hydraulic fracturing. It ensures that the material cost is reduced while the amount of fracturing fluid is increased. In addition, the multi-stage proppant combination is used to support all levels of fractures, which improves the conductivity of all levels of fractures. During the implementation of refracturing, the amount of fluid used in single layer is gradually increased, from 2300 to 3500 cubic meters, the maximum amount of fracturing fluid injected in single layer is 10000 cubic meters, and the proportion of slippery water is increased from 80% to 95%. The proppant is composed of 100/140 mesh and 40/70 mesh ceramic proppant, with an average sand content of 97.7 cubic meters per layer. From the perspective of construction data, after increasing the amount of fracturing fluid used in single well, the average pump stopping pressure of the later batch of construction wells is increased by 3.5 Mpa and the construction pressure is increased by 4.5MPa. After adding temporary plugging agent, the average construction pressure increased by 1.8 MPa, and the opening characteristics of new joints were obvious. After refracturing, all test wells are produced by automatic injection production, the total number of automatic injection production days is 5.2 times of the initial fracturing, and the cumulative oil production is 1.5 times of the initial fracturing. Through practice, the original injection production relationship is broken. Increasing the amount of fracturing fluid can not only supplement the formation energy, but also improve the complexity of fractures. The multi-stage proppant slug can significantly improve the conductivity of fractures at all levels, prolong the life cycle of old wells, and provide technical support for multi thin layer reconstruction.
In the whole lifecycle of reservoir development, periodic intervention in wells is the daily work of reservoir management, which is essential to production maintenance and workover activity. The identification of actionable plan at well-by-well level is time consuming and inefficient, especially for reservoirs with a considerable amount of wells. Over-reliance on engineer experience also increase uncertainties over reliable plan. The workflow for candidate screening provides a systematic and efficient approach to dealing with this issue. Prior to commencing the process, reservoir static model and dynamic model were updated to meet recent reservoir performance. The first step was to identify potential wells in two ways, including the typical diagram indicating the relationship between production performance and reservoir properties, and the modified heterogeneity index method introduced by Del Castillo et al. After completing candidate recognition, diagnostic analysis was conducted to determine root causes through dynamic analysis of injection/production performance at well/pattern level. Finally, comprehensive evaluation and forecast for workover activities were carried out in terms of technical and economic aspects, which will facilitate appropriate decision making. This workflow has successfully been applied to a giant heterogeneous carbonate reservoir with gas cap. The identified candidates can be categorized into four types. The whole/partial gas cusping wells with a sharp/gradual increasing trend in gas-oil ratio (GOR) are influenced by gas cap. The gas channeling wells with uneven sweep efficiency are attributed to the injected gas overriding in heterogeneous reservoir. The water cusping wells with medium water cut are influenced by bottom aquifer. Accordingly, an integrated optimization plan is proposed to mitigate the outlined risks. The recompletion strategy with Autonomous Inflow Control Device (AICD) and sliding sleeves is recommended for gas/water cusping wells, and results are phenomenal in terms of segmented isolation of high GOR/water cut intervals and delaying gas/water breakthrough. The converting from gas injection to tapered water-alternating-gas (TWAG) through increasing the ratio of water-to-gas in a step wise process has been implemented for gas channeling wells, and an improved conformance is observed. The TWAG project appears to be promising because of high gas/water utilization efficiency and reduced gas cost. This methodological approach provides a generic workflow for conducting an integrated analysis of workover candidates screening and plan making. Reservoir performance will be monitored and maintained in order to ensure efficient reservoir management practice.
In a Middle East oilfield, reservoirs are characterized by high temperature, high salinity, high CO2 / H2S content, and low pH, which leads to harsh corrosive environment. With development of the field, the increasing water cut and application of CO2-EOR technology have made tubulars face greater corrosion risk. Therefore, employing feasible anti-corrosion coating to corresponding part is one of the most effective technologies to mitigate downhole corrosion risk, reduce workover, and avoid potential HSE risk. Corrosion environment characteristics was thoroughly studied by reviewing production history, water chemistry, gas composition, downhole temperature and pressure, logging data, etc. Downhole corrosion condition was classified based on NACE standard RP0775-2005. Based on this, the field simulated corrosion tests were carried out on the self-healing coating in high-temperature and pressure autoclave. The self-healing coating was fabricated by loading slow-released MBT-LDH nanocomposites to the phenolic epoxy resin. For comparison, the similar experiment was also conducted on commercial phenolic epoxy coating and heavy-duty coating. The anti-corrosion performance and applicability of the coatings were characterized by SEM/EDS, FT-IR and EIS. Two main factors have been considered while evaluating the coating options, the first consideration is reliability and durability of the coating. If the coating is easily damaged during operation and transportation, its protective performance decreases after damage, which cannot be easily repaired again. The second consideration is the compatibility of the coating in a harsh downhole environment. Considering the above aspects, the self-healing coating, commercial phenolic epoxy coating and commercial heavy-duty were selected. After corrosion tests, a small amount of corrosion products can be observed on the commercial phenolic epoxy coating surface both in the simulated well head and bottom condition. There were no obvious morphology changes on the heavy-duty coating surface in both condition, however, chemical degradation of the coating was observed in well bottom condition. Notably, the self-healing coating appeared no peeling, bubbling and other defects in both conditions. There were corrosion products identified in the pre-destructed area of the coating, which attributed to the localized inhibition of the self-healing coating. This paper investigated the corrosion resistance coating technology, including coating selection evaluation, typical tubing thread area protection technique, coating chemical and physical property analysis and evaluation. The study also recommended coating applicability for the target reservoir. The results suggested that phenolic epoxy based self-healing coating show robust anti-corrosion performance and can be used in the downhole containing CO2 and H2S.
Water cut (WCT) is a key parameter to analyse the performance of wells and reservoirs within a producing oilfield. However, the WCT data recorded in the life term of a well may not always be accurate or available, which may lead to the potential problem with well and reservoir models constructed with the data. This can lead to errors in predicted future well and field production, or missed opportunities for well workover activities. This paper describes a case study where the WCT of producing oil wells from a large Middle Eastern oil reservoir was modeled using random forest regression in order to identify errors and improvements in the field data. Pressure data and fluid properties were input as training variables and the model was evaluated by cross-validation. The relative importance of these variables was calculated and the coefficient of determination (R2) between the observed and predicted WCT of the test set was used to evaluate the model performance. It was found that the apparent density of the producing fluid and the variables related to the fluid composition have strong connections with WCT, as would be expected based on traditional vertical pipe flow theory. For the wells with good field WCT data the model accurately matched the real field data. For the wells with poor or absent field WCT data the model was used to predict the WCT and significantly enhance the dataset with a high degree of confidence. It is concluded that the random forest regression model can predict the WCT based on other well surveillance data. Overall, the current study provides an approach to integrate multiple factors of surveillance data to calibrate the WCT data, and can add significant value to well and reservoir models for the purpose of accurate production dynamics analysis and forecasting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.