page_title: Wireline QA/QC
section_title: Introduction
hierarchical_section_title: Wireline QA/QC / Introduction
caption_attribution_description: English: Wireline log composite for the Lisburn 1 well, drilled by Husky Oil in the Alaska Petroleum Reserve, between June 1979 and May 1980
context_page_description: Wireline quality assurance and quality control is a set of requirements and operating procedures which take place before, during, and after the wireline logging job. The main merits of wireline QA/QC include accuracy and precision of recorded data and information. Accuracy is a measure of the correctness of the result and is generally depended on how well the systematic errors are controlled and compensated for. Precision is depended on how well random errors are analysed and overcame.
context_section_description: Wireline logging is a part of exploration geophysics and is mainly used to detect the presence of economically useful hydrocarbons in the Earth’s sub-terrain. Products of wireline logging are wireline logs or well logs.: (Fig. 1. Ll1LOG)
   In the oil industry the logs are “a recording against depth of any of the characteristics of the rock formations traversed by a measuring apparatus in the well-bore”. The well logs are obtained by lowering the measuring tools on a wireline (cable) into the well (borehole). The integral parts of wireline logging operations are quality assurance and quality control procedures. Quality control is the “process that defines how well the solution for a specific problem is known”. Well log quality control is a “set of methods that identifies and analyses data deviations from established standards and allows the design of a remedy”.
  Unlike measurements in well-known and controlled laboratory conditions, logging is performed in-situ and can be affected by different possible failure sources and susceptible to systematic and random errors. The objective of wireline logging job is to obtain a permanent continuous record of the rock properties penetrated by the wellbore with the end result of wireline logs, fluid, and rock samples. Of all the well data sets recorded and collected, well logs are the most valuable as they are vital for reservoir and formation evaluation.
  Wireline (well) logs are then combined with drilling data, mud logs, and measurements while drilling (MWD) and coring information in order to choose correct testing and completion intervals to properly evaluate the production potential of the well. There are two categories of well log data: the original data (e.g. Gamma Ray log as a result of gamma rays measurements in the borehole, through an iodine crystal scintillation detector, calibrated as per normal field operational procedure) or derived data (data resulting from the processing of the original data, e. g. calculating the volume of shale).
  Main components of the well log data record are logs themselves (main curves for the main and repeat sections with relevant information - calibration information, parameter tables… and additional curves of the main and repeat passes including down-logs and images of quality control logs)  and contextual information, such as data acquisition plans, other job reports, witness reports, and tool specification. Contextual data is of a great value for exploration but can be lost or difficult to access.
  With the best quality wireline logging data acquired, subsequent steps in well production and completion are more precise and effective. High quality data and conscientious data management enables the prognosis of potential problems and failures so the whole process (the whole rig or oilfield lifetime) can be adapted and configured in order to prevent possible consequences in regard to human safety, environmental preservation, and infrastructural integrity. Acquisition of geotechnical and petrophysical data is costly, but necessary. Data of dubious quality cannot yield reliably good decisions. The poorer the quality of data, the higher risk associated with decisions based upon them. The less knowledge there is about the quality of recorded and collected data, the higher is the uncertainty of said decisions and can lead to false interpretations and evaluations. A good evaluation is only possible with good quality data so it is essential to acquire the best quality data.
caption: LI1LOG
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