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Peregrino is a heavy oil field in the Campos basin offshore Brazil. The field started production in 2011, and Phase 2 was on stream in 2022. More development drilling is ongoing. The oil viscosity in Phase 2 has large variations from limited exploration wells, ranging from 30 to 180 cp. Any changes in the viscosity in the reservoirs can lead to a large difference in oil recovery. Therefore, updating the viscosity distribution in the reservoirs along with the development drilling is important. Different methods can acquire reservoir oil viscosity, including downhole logging and sampling, mud gas, extracts from cuttings, and surface oil sampling. Our previous studies demonstrate that mud gas provides real-time and continuous reservoir oil properties. Due to the use of water-based mud in the development drilling and relatively high degasser temperature, the standard mud gas data has been of good quality come to light gas components C1 to C3. Standard mud gas logging is part of the mud logging service, and there is no additional cost to acquire the data. Can we develop a simple approach to predict the oil viscosity based on the "free" standard mud gas data? A thorough study has been performed based on the reservoir fluid database from the Peregrino field. The results show the methane/ethane and methane/propane ratios are the best parameters correlated to reservoir oil viscosity. Before adopting the new method using standard mud gas, we extensively compared results with the measurement of PVT (Pressure Volume Temperature) samples and pressure points. The comparison shows that the simple approach based on standard mud gas provides an oil viscosity classification that distinguishes between high and low-viscosity fluids along a given well. The threshold for the two categories is identified from the reservoir fluid database, and the results from the mud gas method are in excellent agreement with the experimental results from the PVT analysis. The latter ones are regarded as the ground truth answer. Therefore, we deployed a simple approach based on standard mud gas data to map oil viscosity for future wells. The new approach using standard mud gas data provides a real-time method to identify the continuous reservoir oil viscosity following the well path without data acquisition cost. Along with drilling more wells, we will soon achieve a detailed and accurate reservoir oil viscosity distribution in different reservoirs. The viscosity mapping of the reservoirs lays the ground for further optimizing the drilling target and well placement and improving the oil recovery.
Peregrino is a heavy oil field in the Campos basin offshore Brazil. The field started production in 2011, and Phase 2 was on stream in 2022. More development drilling is ongoing. The oil viscosity in Phase 2 has large variations from limited exploration wells, ranging from 30 to 180 cp. Any changes in the viscosity in the reservoirs can lead to a large difference in oil recovery. Therefore, updating the viscosity distribution in the reservoirs along with the development drilling is important. Different methods can acquire reservoir oil viscosity, including downhole logging and sampling, mud gas, extracts from cuttings, and surface oil sampling. Our previous studies demonstrate that mud gas provides real-time and continuous reservoir oil properties. Due to the use of water-based mud in the development drilling and relatively high degasser temperature, the standard mud gas data has been of good quality come to light gas components C1 to C3. Standard mud gas logging is part of the mud logging service, and there is no additional cost to acquire the data. Can we develop a simple approach to predict the oil viscosity based on the "free" standard mud gas data? A thorough study has been performed based on the reservoir fluid database from the Peregrino field. The results show the methane/ethane and methane/propane ratios are the best parameters correlated to reservoir oil viscosity. Before adopting the new method using standard mud gas, we extensively compared results with the measurement of PVT (Pressure Volume Temperature) samples and pressure points. The comparison shows that the simple approach based on standard mud gas provides an oil viscosity classification that distinguishes between high and low-viscosity fluids along a given well. The threshold for the two categories is identified from the reservoir fluid database, and the results from the mud gas method are in excellent agreement with the experimental results from the PVT analysis. The latter ones are regarded as the ground truth answer. Therefore, we deployed a simple approach based on standard mud gas data to map oil viscosity for future wells. The new approach using standard mud gas data provides a real-time method to identify the continuous reservoir oil viscosity following the well path without data acquisition cost. Along with drilling more wells, we will soon achieve a detailed and accurate reservoir oil viscosity distribution in different reservoirs. The viscosity mapping of the reservoirs lays the ground for further optimizing the drilling target and well placement and improving the oil recovery.
Drill cuttings are readily available for all wells we drill. Geochemical analysis has been employed to estimate key oil properties, such as API density and viscosity. However, most studies focus on drill cuttings with water-based mud. Identifying reservoir fluids in highly contaminated drill-cutting samples becomes a significant challenge when drilling wells with oil-based mud. Consequently, there is a high business demand for predicting reservoir fluid properties from drill cuttings with oil-based mud. In 2015, Gel Permeation Chromatography (GPC) coupled with ultraviolet (UV) absorbance detection was introduced in the upstream industry. Elias and Gelin demonstrated the capability of the GPC-UV method to predict API gravity from drill-cutting samples with oil-based mud in unconventional reservoirs. This study extended the GPC-UV approach to conventional reservoirs across multiple fields from the Norwegian Continental Shelf and other global assets. We developed a multiple-wavelength method instead of fixed wavelength detection to explore correlations between GPC-UV detections and reservoir fluid properties. The drill cuttings used in this study are from multiple fields from the Norwegian Continental Shelf and other global assets, where oil-based mud was consistently used for well drilling. Consequently, extracts from these cutting samples are contaminated by oil-based mud. Utilizing the GPC-UV method revealed clear oil peaks with the oil-based mud response appearing on the baseline. Correlating these results with GPC-UV data from stock tank oil samples and known reservoir fluid properties enables qualitative determination of fluid type (gas, oil, or water) and estimation of API from new drill cutting samples. A digital solution based on machine learning, leveraging broad GPC-UV measurements, is needed to improve prediction accuracy further. While ongoing studies aim to establish a comprehensive database of GPC-UV measurements for stock tank oil and drill-cutting extracts, the GPC-UV method demonstrates impressive potential for analyzing reservoir fluids in challenging drill-cutting samples. Given the widespread availability of drill-cutting samples, this new method offers a cost-efficient and accurate means of determining reservoir fluid properties without resorting to downhole measurements or sampling. This method could fulfill the vision of considering "every piece of cutting as a PVT sample," with applications ranging from well placement and reservoir management to production optimization, flow assurance, and plug & abandonment.
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