How can you choose the best well logging method?

1 Objectives and data requirements

The first step in choosing the best well logging method is to define your objectives and data requirements. What are you trying to achieve with well logging? What kind of information do you need to make decisions or solve problems? For example, if you want to evaluate the porosity, permeability, and saturation of a reservoir, you might need a combination of open-hole logging methods, such as resistivity, sonic, density, and neutron logs. If you want to monitor the performance of a producing well, you might need a cased-hole logging method, such as production logging or pressure transient testing.

2 Operational and environmental constraints

The second factor to consider is the operational and environmental constraints that might affect your well logging method selection. What are the technical and logistical challenges that you face in your well site? How can you overcome them or mitigate them? For example, if you have a high-temperature or high-pressure well, you might need a special logging tool that can withstand the harsh conditions. If you have a deviated or horizontal well, you might need a logging tool that can be conveyed by wireline, coiled tubing, or drill pipe. If you have a limited budget or time, you might need a logging tool that can provide fast and reliable data.

3 Data quality and reliability

The third factor to consider is the data quality and reliability that you can expect from your well logging method. How accurate and precise are the measurements that you obtain? How consistent and repeatable are they? How sensitive and responsive are they to the changes in the subsurface parameters? For example, if you want to measure the formation resistivity, you might need to account for the effects of borehole size, mud type, invasion depth, and tool calibration. If you want to measure the formation density, you might need to account for the effects of borehole rugosity, mud cake, standoff, and environmental corrections.

4 Data analysis and interpretation

The fourth factor to consider is the data analysis and interpretation that you need to perform on your well logging data. How easy and straightforward are the methods and models that you use to process and evaluate your data? How robust and reliable are the assumptions and parameters that you use to apply them? How compatible and complementary are they with other data sources and methods? For example, if you want to estimate the formation porosity, you might need to use different porosity models depending on the rock type, mineralogy, fluid type, and saturation. If you want to estimate the formation permeability, you might need to use different permeability models depending on the flow regime, pore geometry, and stress state.

5 Data integration and optimization

The fifth factor to consider is the data integration and optimization that you can achieve with your well logging method. How well can you combine and correlate your well logging data with other data sets, such as seismic, core, production, and test data? How well can you use your well logging data to optimize your reservoir characterization, modeling, and management? For example, if you want to map the reservoir structure and continuity, you might need to integrate your well logging data with seismic data using seismic-to-well ties, synthetic seismograms, and inversion techniques. If you want to optimize your reservoir performance and recovery, you might need to use your well logging data to calibrate your reservoir simulation models, design your well placement and completion, and plan your enhanced oil recovery strategies.

6 Cost-benefit analysis

The sixth and final factor to consider is the cost-benefit analysis that you need to conduct on your well logging method. How much does your well logging method cost in terms of equipment, personnel, time, and risk? How much value does your well logging method add in terms of information, insight, and impact? How can you balance the trade-offs and maximize the returns on your well logging investment? For example, if you want to reduce the uncertainty and risk in your reservoir appraisal and development, you might need to weigh the costs and benefits of acquiring more or less well logging data, using more or less sophisticated well logging tools, and applying more or less advanced well logging techniques.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?