The concept of a data base is not new in the oil industry. Data collection, storage, and retrieval of single-well data, field data, and general information are practiced by most oil companies. A field usually contains a wealth of information in the form of log, core, geological, geophysical, test, and production data, and these should be used collectively to enhance the understanding of the reservoir's geometry and dynamics. At present, most items of data are collected and processed independently. What has not been effectively achieved is a dynamic data base in which all the data can be interacted and efficiently used to obtain field maps and grids, well-to-well correlations, and transforms to optimize data in wells where data are limited.
This paper discusses the principle, structure. and application of a dynamic data base that allows data to be not only retrieved and displayed, but also used to evaluate trends, calibrate and reinterpret new and old data, and optimize both the single-well and field results. Additional data are readily integrated into the system; in addition, the data base can be used to check and calibrate new data and then to update existing field models, trends, and grids. Statistical data banks can be created and used to optimize the information from old logging suites and to estimate missing parameters, such as permeability.
Field and reservoir zone parameters can be modified easily. Output data, in the form of tabulations, maps, and grids, can be obtained readily and used as input data in reservoir simulation. Examples that demonstrate how the data base can be used effectively by all levels of management are presented.
What is a data base? Any collection and organization of data on tapes, hard copies and files, or a computer may be called a data base. In constructing a data base, four important questions need to be addressed.
What Type of Data Will be Stored in the Data Base? Data stored within a database system can be divided into two groups.
Zone and Field Data (Macrodata). Data concerning formations, zones within formations, subzones within zones, and such parameters as average porosity, permeability-thickness, kh, pressure, p, productivity index, and volume of hydrocarbon fall into this category. General data relating to the field and to each well (such as well coordinates, mean sea level, and kelly bushing) are also covered in this group. These data can take the form of numbers, names, and codes, such as the name of fields (e.g., Zakum and Asab), geographical locations (e.g., land and offshore), formation names (e.g., Arab and Thamama), and zone and subzone divisions (e.g., Zones A and B and Subzone A1).
Well Data (Microdata). This category includes high-sampling-rate data such as
log data (raw ocomputer-processed) that arusually indexed to depth and usually sampled every 1/2 ft [0.15 m],
core data that are also indexed to depth, and
other high-sampling-rate data that are usually indexed to depth or time (e.g., well test data, mud and cuttings log, and drilling rate).
For the purpose of clarity, these two types of data will be referred to in all subsequent discussions as macro- and microdata, respectively. A large proportion of the macrodata is derived from the microdata. The volume of the reservoir is derived by integrating the depth-indexed porosity values from computed log data stored as microdata. Various reservoir volumes may be desired if there are different porosity cutoffs. The volume of hydrocarbon is derived by integrating the sum of porosity and hydrocarbon saturation. Different cutoff values may be used. Many other parameters, like kh and volume of moved hydrocarbon (MHC), can be derived similarly.
Who Will Use This Data Base? If a data base is to be used successfully, it must serve the needs of management for monitoring and control, of specialists for technical applications, and of technical personnel for report compilation.
How Flexible and Dynamic Is the Selected Data Base? The unique nature of petrophysical data demands a specially designed data base structure. Thus, the initial framework and design of a data base are the most important steps. A general-purpose business database package often is used to handle both the macro- and microdata. package often is used to handle both the macro- and microdata. This can lead to a slow, inflexible system. In addition, such a data base may be difficult to maintain and upgrade.
