In making the petrophysical calculations of lithology, net pay, porosity, water saturation, and permeability at the reservoir level, the development of a complete petrophysical database is the critical first step. This section describes the requirements for creating such a database before making any of these calculations. The topic is divided into four parts: inventory of existing petrophysical data; evaluation of the quality of existing data; conditioning the data for reservoir parameter calculations; and acquisition of additional petrophysical data, where needed. The overall goal of developing the petrophysical database is to use as much valid data as possible to develop the best standard from which to make the calculations of the petrophysical parameters. The second step in working with the petrophysical data is to evaluate the quality of each of these types of data. This step requires that the data inventory and database preparation steps are completed first so that this second step can occur as a systematic and complete process. The evaluation process is a "compare and contrast" exercise. The evaluation of log-data quality has many aspects. This should be noted in the petrophysical database. "Flags" of various types should be stored, for example, to denote intervals where the hole size exceeds some limit, or where there is cycle-skipping on the sonic logs. Logging tools sometimes become temporarily stuck as a log is being run. When the tool is stationary, each detector on it becomes stuck at a different depth, so the interval of "stuck" log will vary for each log curve. For example, the neutron log typically sticks over an interval approximately 10 ft above the stuck interval on a density log. It may be possible to "splice" in a replacement section of log from a repeated log section, or the invalid readings may simply be deleted. Second, each log is formally calibrated before the start of each logging run by various calibration standards. The logs are also checked again after the run. Calibration records may assist in determining the quality of the logs. Perhaps of equal importance are the written comments on the log heading made immediately after the job by the logging engineer. Third, systematic influences on the quality of log readings should be corrected. For example, if some of the wells are drilled with water-based mud (WBM), the effect of WBM-filtrate invasion on various resistivity logs can be quantified. This is done by computations made using the various resistivity logs in the same wellbore; however, where deep invasion of WBM filtrate occurs, offsetting wells drilled with oil-based mud (OBM) give a good comparison. The induction logs in OBM wells can provide accurate true reservoir resistivity values in thick hydrocarbon zones. See the chapter on resistivity and SP logging in this volume of the Handbook for more information on how invasion effects can be handled. Boreholes are not always right cylinders.