Converting WITS Data to WITSML: Necessity and Methods

Necessity of Data Conversion and Aggregation

The conversion of WITS data to WITSML is necessary for several reasons in the oil and gas industry. WITS, developed by the American Petroleum Institute (API) in the early 1980s, is a binary format for point-to-point transfer of well data. Although efficient for its time, this standard has limitations such as the lack of a standard programming interface (API), a limited number of data objects, and reliance on serial transfer of ASCII data. In contrast, WITSML uses modern web technologies such as XML, SOAP, and ETP and enables data exchange in complex and multilateral environments. According to Energistics, WITSML, as an open and non-proprietary standard, is designed for oil companies, service providers, drilling contractors, software vendors, and regulatory bodies to facilitate the free flow of technical data across networks.

One of the most important reasons for the necessity of converting WITS data to WITSML is the need for data standardization. WITS, due to its use of a binary format and the absence of a standard structure for data objects, often leads to data inconsistencies between different systems. For example, in WITS data transfer, both parties must agree on the meaning of each record (such as Bit Depth or rate of penetration), which can lead to interpretation errors. WITSML addresses this problem by providing standard XML schemas, which enables the exchange of integrated data between different systems.

Another reason is WITSML's ability to integrate with emerging technologies. WITSML is compatible with cloud platforms like OSDU and advanced analytics systems such as Artificial Intelligence and Machine Learning. This integration allows companies to store, analyze, and share well data on a large scale. For example, WITSML data can be fed into predictive algorithms to forecast potential problems such as well instability or equipment failure. These capabilities are not possible with WITS due to its technical limitations.

Data aggregation is also a key aspect of the conversion's necessity. Many oil companies have vast repositories of WITS data that have been collected over decades. If converted to WITSML, this data can be integrated with newer data and used in modern platforms like OSDU. This aggregation enables more comprehensive analyses, such as comparing historical and real-time data to optimize drilling operations. According to Energistics, WITSML version 2.1 is aligned with the OSDU data model, which makes data conversion and aggregation easier for digital projects.

Finally, converting to WITSML helps improve collaboration among organizations. In oil and gas projects involving multiple contractors, service providers, and regulatory bodies, WITSML acts as a common language, enabling data exchange without the need for manual conversions or intermediary software. This reduces operational costs and increases efficiency.

Data Conversion Methods

Converting WITS data to WITSML requires technical approaches that are chosen based on project needs, existing infrastructure, and data types. Energistics provides tools and guidelines to facilitate this conversion, and various companies have developed software and services for this purpose. The following are the main methods for converting WITS data to WITSML.

Manual Conversion and Use of Open-Source Tools

One of the conversion methods is to use open-source tools such as the LAS to WITSML converter software provided by Energistics. Although this tool is specifically designed to convert LAS (Log ASCII Standard) files to WITSML, it can be used as a template for WITS data conversion. This tool includes Java packages and mapping resources that convert input data to the standard WITSML XML format. For WITS conversion, developers can use the XML schemas (XSD) provided by Energistics to map binary WITS data to WITSML data objects such as WellLog or MudLog.

For example, WITS data containing simple records like bit depth or well pressure can be manually mapped to WITSML objects. This process involves reading the binary WITS data, identifying the records (e.g., Record 01, Item 08 for Bit Depth), and converting them to the XML structure using WITSML schemas. Energistics recommends using XML data samples (such as the data donated by Statoil in 2016) for testing and validation.

Using Automated Conversion Tools

Automated conversion tools like UniDAQ provide a simple and efficient way to convert WITS data to WITSML. UniDAQ is a compact device that converts WITS, OPC UA, MODBUS, and OSI PI data to WITSML or ETP. This tool collects WITS data from various sources and converts it to the standard WITSML XML format without the need for specialized training. UniDAQ supports time-based and depth-based data and can be configured locally or remotely, which reduces operational costs.

For example, in a drilling project, UniDAQ can receive WITS data from well sensors and convert it to a WellLog or Trajectory object in WITSML. This data is then transferred via the ETP protocol to a central server or cloud platform like OSDU. This method is particularly suitable for projects that require fast and human-free conversion.

Using Software Libraries

Software libraries such as Petrolink.WitsmlConverter and WitsmlObjectsLibrary (developed by Hashmap) are used to convert WITSML data between different versions (e.g., 1.3.1.1, 1.4.1.1, and 2.0) and also to convert WITS data to WITSML. These libraries, typically written in programming languages like C# or Java, support XML transformations and post-conversion processing. To convert WITS to WITSML, the binary WITS data must first be converted into an intermediate format (like CSV or JSON), and then mapped to WITSML objects using these libraries.

For example, the Petrolink.WitsmlConverter library first parses the input data, then uses XML transformations to convert it to the desired WITSML version (e.g., 2.1). This library also adjusts the units of measure (uom) between different WITSML versions to ensure compatibility. This method is suitable for projects that require large-scale conversion of legacy WITS data.

Integration with Data Management Systems

Another method is to integrate WITS data with data management systems that support WITSML. For example, systems like TIBCO StreamBase or Kongsberg Digital’s SiteCom use WITSML APIs such as WMLS STORE to read, write, and delete data. In this method, WITS data is first converted to an intermediate format (like CSV) and then imported into the system via WITSML APIs. This method is especially suitable for projects where WITS data needs to be integrated with newer WITSML data.

For example, TIBCO StreamBase uses WITSML operators like Read Log and Log Data Converter to convert string data to data tuples. These operators convert WITS data into WITSML objects like WellLog and enable storage in databases such as PostgreSQL or TimescaleDB. This method allows for the aggregation of data into a central repository and facilitates advanced analytics.

Cloud-Based Conversion

With the advent of cloud platforms like OSDU, the conversion of WITS data to WITSML can be performed in cloud environments. IBM Cloud Pak for Data is one of the tools that enables the conversion of WITSML data to OSDU-compatible formats. In this method, WITS data is first converted to an intermediate format and then mapped to WITSML objects. This data is then loaded into the OSDU storage layer, which allows for large-scale analysis and integration with other standards like PRODML and RESQML.

For example, WITS data related to bit depth can be converted to the Trajectory object in WITSML and stored in a cloud repository. This method allows companies to aggregate historical and real-time data in a single platform and use advanced analytical tools. Energistics emphasizes that WITSML version 2.1 is specifically designed for alignment with OSDU, which makes data conversion and aggregation easier.