PVT data and reports are essential for reservoir engineering, as they provide information on the fluid properties and behavior of oil and gas in the subsurface. However, not all PVT data and reports are equally reliable and accurate. How do you evaluate the quality and reliability of PVT data and reports? Here are some tips and best practices to help you.
The first thing to check is the source and origin of the PVT data and reports. Where did they come from? Who collected and analyzed them? How recent are they? Ideally, you want to use PVT data and reports that are derived from actual reservoir samples, not from correlations or extrapolations. You also want to use PVT data and reports that are produced by reputable laboratories or service providers, following industry standards and quality control procedures. Finally, you want to use PVT data and reports that are relevant and representative of the reservoir conditions and fluid composition, not outdated or mismatched.
Evaluate the quality and reliability of PVT data and reports by assessing the laboratory procedures, ensuring proper sample handling, verifying calibration standards, checking for consistency in measurements, and comparing results with historical data or industry benchmarks. Rigorous quality control and adherence to standard protocols during the PVT analysis process contribute to the reliability of the data and the overall accuracy of the PVT reports.
The origin of the sample and especially the conditions under which it is taken for PVT analysis is more related to the representativeness of the sample with respect to the reservoir fluid. It is essential to ensure that the fluid conditions are maintained and reproduced in the laboratory and that the sample is in a single-phase state.
The next thing to check is the sampling and analysis methods used to obtain the PVT data and reports. How were the reservoir fluid samples collected, transported, stored, and prepared? How were the PVT experiments conducted, measured, and recorded? What equipment and instruments were used? How were the uncertainties and errors estimated and reported? You want to use PVT data and reports that are based on proper sampling and analysis methods, following best practices and guidelines. You also want to use PVT data and reports that are transparent and detailed about the methods, equipment, and uncertainties involved, not vague or incomplete.
Non-bottom samples should be avoided as far as possible and it should be ensured that the pressure at which the sample is taken is above the saturation point.
The third thing to check is the consistency and compatibility of the PVT data and reports. Do they match and agree with each other and with other sources of information, such as well logs, core analysis, production data, or reservoir models? Do they show reasonable and realistic trends and values, such as bubble point, saturation pressure, formation volume factor, viscosity, compressibility, or density? Do they fit the reservoir objectives and scenarios, such as recovery mechanism, depletion strategy, or enhanced oil recovery method? You want to use PVT data and reports that are consistent and compatible with the reservoir context and data, not contradictory or unrealistic.
The fourth thing to check is the sensitivity and uncertainty of the PVT data and reports. How sensitive are the PVT data and reports to changes in reservoir parameters, such as temperature, pressure, composition, or phase behavior? How uncertain are the PVT data and reports due to measurement errors, experimental limitations, or data variability? How do these sensitivity and uncertainty affect the reservoir performance and recovery estimates, such as reserves, production rates, or recovery factors? You want to use PVT data and reports that are robust and reliable under different reservoir conditions and scenarios, not sensitive or uncertain to the point of affecting the reservoir decisions and outcomes.
Sensitivity analysis examines how variations in PVT data inputs (e.g., pressure, temperature, composition) influence outputs like phase behavior and fluid properties. It identifies critical parameters affecting results. Uncertainty analysis quantifies reliability by assessing measurement uncertainties, experimental errors, and result variability using methods such as Monte Carlo simulations.
The fifth thing to check is the validation and verification of the PVT data and reports. How have the PVT data and reports been validated and verified by independent or alternative sources, such as field tests, laboratory tests, or numerical simulations? How have the PVT data and reports been compared and calibrated with historical or actual reservoir behavior and performance, such as pressure decline, gas-oil ratio, or water cut? How have the PVT data and reports been updated and revised based on new or additional data or information? You want to use PVT data and reports that have been validated and verified by multiple sources and methods, not based on assumptions or hypotheses.
The sixth thing to check is the communication and presentation of the PVT data and reports. How are the PVT data and reports communicated and presented to the relevant stakeholders, such as reservoir engineers, geologists, managers, or regulators? How are the PVT data and reports summarized and visualized in tables, charts, graphs, or maps? How are the key findings, implications, and recommendations of the PVT data and reports highlighted and explained in clear and concise language? You want to use PVT data and reports that are communicated and presented in an effective and efficient way, not in a confusing or misleading way.