Integration of Downhole Fluid Analysis and Advanced Mud Gas Logging Reduces Uncertainty in Reservoir Evaluation
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Mud-gas technologies for continuous PVT-like analysis of reservoir fluids in the drilling mud require a calibration procedure to determine the efficiency of the gas extraction process. This procedure is required because the efficiency of the hydrocarbons extraction process is strongly affected by the drilling mud type and properties, and so it must be performed any time the mud significantly changes. The calibration procedure requires a sample of drilling mud that contains significant amounts of alkanes. Currently, this sample is collected while drilling during a gas peak and stored until the end of the phase, when the calibration can be performed. Thus, the gas extraction efficiency can only be determined at the end of each drilled section, and the quantitative analysis of the reservoir fluid in the mud is made available only at the end of each section. This paper presents a new procedure, in which a Calibration Mud sample is built by injecting and emulsifying several alkanes into the mud. The calibration can then be performed at any time before drilling commences. It is extremely difficult to inject and dissolve gaseous light hydrocarbons into a mud sample at the rigsite. For this reason, we inject a sample of six liquid alkanes into the mud and emulsify it to build a mud sample suitable for the calibration procedure. The extraction efficiencies for the lighter gas alkanes are then extrapolated from those of the injected alkanes using a model of the extraction process. The new calibration process has been tested in several wells around the world. In each test, the new calibration process and standard calibration (performed at the end of the phase using mud collected while drilling) were performed. Validation of the new technique comes from ensuring the extraction efficiency coefficients using our new calibration mud match those coming from the standard calibration. The results were conclusive with similar coefficients obtained in each test. The uncertainty intervals overlap, and the calibration coefficients are statistically equivalent. The new calibration procedure represents an innovative methodology enabling real-time, continuous quantification of the light hydrocarbons content (C1-C6) of the reservoir fluid, comparable to the PVT monophasic composition, while drilling, at surface. This is the first time that such data can be delivered in real-time while drilling. The resulting measurements have multiple applications such as enhanced geosteering and well placement, real-time identification of gas-oil contacts, and real-time selection of sampling points and can be integrated with downhole tool measurements to provide a true real-time understanding of the subsurface fluids.
Mud-gas technologies for continuous PVT-like analysis of reservoir fluids in the drilling mud require a calibration procedure to determine the efficiency of the gas extraction process. This procedure is required because the efficiency of the hydrocarbons extraction process is strongly affected by the drilling mud type and properties, and so it must be performed any time the mud significantly changes. The calibration procedure requires a sample of drilling mud that contains significant amounts of alkanes. Currently, this sample is collected while drilling during a gas peak and stored until the end of the phase, when the calibration can be performed. Thus, the gas extraction efficiency can only be determined at the end of each drilled section, and the quantitative analysis of the reservoir fluid in the mud is made available only at the end of each section. This paper presents a new procedure, in which a Calibration Mud sample is built by injecting and emulsifying several alkanes into the mud. The calibration can then be performed at any time before drilling commences. It is extremely difficult to inject and dissolve gaseous light hydrocarbons into a mud sample at the rigsite. For this reason, we inject a sample of six liquid alkanes into the mud and emulsify it to build a mud sample suitable for the calibration procedure. The extraction efficiencies for the lighter gas alkanes are then extrapolated from those of the injected alkanes using a model of the extraction process. The new calibration process has been tested in several wells around the world. In each test, the new calibration process and standard calibration (performed at the end of the phase using mud collected while drilling) were performed. Validation of the new technique comes from ensuring the extraction efficiency coefficients using our new calibration mud match those coming from the standard calibration. The results were conclusive with similar coefficients obtained in each test. The uncertainty intervals overlap, and the calibration coefficients are statistically equivalent. The new calibration procedure represents an innovative methodology enabling real-time, continuous quantification of the light hydrocarbons content (C1-C6) of the reservoir fluid, comparable to the PVT monophasic composition, while drilling, at surface. This is the first time that such data can be delivered in real-time while drilling. The resulting measurements have multiple applications such as enhanced geosteering and well placement, real-time identification of gas-oil contacts, and real-time selection of sampling points and can be integrated with downhole tool measurements to provide a true real-time understanding of the subsurface fluids.
Mud gas data from drilling operations provide the very first indication of the presence of hydrocarbons in the reservoir. It has been a dream for decades in the oil industry to predict reservoir gas and oil properties from mud gas data, because it would provide knowledge of the reservoir fluid properties in an early stage, continuously for all reservoir zones, and at low costs. Previous efforts reported in the literature did not lead to a reliable method for quantitative prediction of the reservoir fluid properties from mud gas data. In this paper, we propose a novel approach based on machine learning which enables us to predict gas oil ratio (GOR) from advanced mud gas (AMG) data. The current work is based on a previous successful pilot in unconventional (shale) reservoirs. Our aim is to extend the results of the pilot study to conventional reservoirs. In general, prediction of reservoir fluid properties is more challenging for conventional reservoirs than for unconventional reservoirs, due to the complexity of petroleum systems in conventional reservoirs. Instead of building a model directly from AMG data, we trained a machine learning model using a well-established reservoir fluid database with more than 2000 PVT samples. After thorough investigation of compositional similarity between PVT samples and AMG data, we applied the model developed from PVT samples to AMG data. The predicted GORs from AMG data were compared with GOR measurements from corresponding PVT samples to assess the accuracy of the GOR predictions. The results from 22 wells with both AMG data and corresponding PVT samples show large agreement between prediction vs. measurement. The accuracy of the predictive model is much higher than previous results reported in the literature. In addition, a Quality Check (QC) metric was developed to efficiently flag low-quality AMG data. The QC metric is vital to give confidence level for GOR prediction based on AMG data when PVT samples are not available. The study confirms that AMG data can be used as a new data source to quantitatively predict continuous reservoir fluid properties in the drilling phase. The method can be used to optimize wireline operations and for some cases, it provides a unique opportunity to acquire reservoir fluid data when conventional fluid sampling or use of wireline tools is not possible. After high-quality PVT data becomes available in the wireline logging phase, the continuous GOR prediction can be further improved and used to determine reservoir fluid gradient and reservoir compartmentalization.
Phase behavior characterization (PVT) and geochemical compositional analysis of petroleum samples play a crucial role in the reservoir evaluation process to help determine producible reserves and the best production strategy. Openhole samples are the most valuable types of samples for PVT and geochemical analysis. Unfortunately, traditional openhole sampling methods are costly and limited to ten to twenty samples, thereby restricting the scope of characterization in a well section. This study summarizes a new microsampling technique for logging while drilling (LWD) and a corresponding wellsite technique to provide compositional interpretation, contamination assessment, reservoir fluid compositional grading, and reservoir compartmentalization assessment. This microscale approach allows fast analysis with a field or near-field deployment of the analytical tool, providing fast turnaround time for analysis. The results inform planning for wireline sample retrieval, if necessary. The microsampler used in the downhole tool is capable of collecting reservoir fluid in small quantities, suitable for compositional analysis. Because of its small size, the microsampler can gather multiple fluids at various reservoir depths, while PVT sampling requires larger volumes and has more constraints. However, when used in combination with conventional PVT-grade samples, the microsamples can provide significant chemical profiling. The quantity of 40 microliters (μl) provides the opportunity to collect many more samples than the conventional PVT sample size of 200 to 1,000 milliliters (ml). Additionally, 40 microliters provides more than enough of a sample for a complete chemical analysis using a liquid chromatograph or gas chromatograph coupled to either a mass spectrometer for biomarker analysis or a flame ionization detector for a complete assay. Isotope analysis is also possible. Recovery to surface of fluid samples collected at reservoir temperature and pressure allows for analysis with an automated gas chromatograph (GC) deployed in the field, providing reduced labor and rapid analysis. The unique injection chamber of the GC is designed with the injection port and valve configured to withstand pressure up to 5,000 psi, which is approximately five times higher than standard GC injection valves. This allows for injection of the microsample with a solvent carrier as a single-phase fluid so that analysis can provide composition and fluid properties, such as gas to oil ratio, without a flash. The GC has two detectors including a flame ionization detector (FID) for hydrocarbon components and thermal conductivity detector (TCD) for inorganic gas components, such as carbon dioxide, nitrogen, and hydrogen sulfide. The system can quantify hydrocarbon components from C1-C36 and perform contamination studies of oil samples with drilling fluids. This study provides a new technique for reservoir engineers to characterize a reservoir completely, without limit to the number of acquired samples. In combination with conventional PVT samples, it is possible to extrapolate the PVT properties to all pump-out stations, and conduct a complete geochemical profile of the reservoir.
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