Project Description

Project Title: CSEM for Geohazard Identification
Prime Performer: National Energy Technology Laboratory
Project Duration: 2019-2021


This project validates and calibrates a new kick detection and fingerprinting concept, by conducting computer simulations and laboratory experiments, to help prevent well blowouts.

A kick represents the first stage of a loss of well control. If left unabated, it can grow in magnitude until a blowout occurs. The best opportunity to prevent a blowout is to suppress the kick as soon as possible. Accurate kick detection and reporting is essential. Conventional kick detection methods are inherently risky, because they require drilling mud from the bottom of the well to the surface so that it can be inspected to determine if formation fluid has mixed with it. This takes time. Existing methods can also increase the risk of fire or explosion if formation fluids have mixed with the drilling mud, because this technique requires personnel to handle additional hazardous materials on the rig floor. Newer kick detection techniques use less risky detection methods, but are too expensive.

A kick detection technique that is inexpensive and accurately conveys critical wellbore information to the driller in a timely manner provides a significant advantage for detecting and suppressing kicks.

This project will conduct computer simulations and laboratory experiments that support validation and calibration of a new kick detection and fingerprinting concept. It will improve the methodology of how a kick affects geophysical signals using both laboratory experiments and numerical simulation by quantitatively identifying the type of kicking fluids, so that correct mitigation actions can be taken. There is currently little understanding beyond theory and anecdotal observations about how a kick affects geophysical signals used in logging while drilling operations. Many variables, such as fluid properties, wellbore geometry, drilling conditions, and geologic properties, can affect the kick signal, but these data are proprietary.


This two-phase, three-year project, will implement two complimentary approaches. The first approach will build and use a modular laboratory-scale apparatus that can simulate the multiphase flow of drilling and kick fluids in a representative geometry. This apparatus will allow the team to verify expected wellbore fluid flow behavior, simulate the expected geophysical response, and provide constitutive models to the numerical simulator and parameter constraints to the kick detection algorithm. The second approach will continue development of a kick detection simulator that will be used to train the kick detection algorithms.

Phase one of this project was the proof-of-concept and it has already been completed. Phase two is the computational modeling, laboratory experimentation, and validation with field data phase. This phase will determine realistic boundaries on all parts of the technology, including detection limits for the geophysical instruments given a kick fluid concentration, assessing instrument response due to multiphase flow behavior in the annulus, and calibration of geophysical instrument responses to specific kick fluid/drilling mixtures.

In the first year of the second phase of this project, most of the work will center on experimental calibration and enhancement of the kick technology. The focus will be on achieving the correct multiphase fluid flow conditions and testing at least one geophysical signal. The team will design a modular experimental apparatus that captures the correct wellbore characteristics. A steady state model for a wide range of drilling fluids without kick events in the annular region of the well will be developed and will be used in predicting downhole flow conditions prior to a kick event. A transient model accounting for a wide range of formation influx conditions will also be developed. This model will predict the annular flow conditions in the downhole region yielding estimates of the multiphase flow parameters, including a model of the mixture properties. The flow conditions and mixture properties will be used to predict the downhole expected measurements from drill string instruments for a range of formation influx fluids and their flow rates. This model will include one geophysical simulation to observe how changes in fluid concentration and in flow regime affect the measured signal.

In the second year, laboratory simulations of mud flows with transient influx of kick fluid will be carried out to validate and improve the model. Specific mud types will be used along with different kick fluid types and flow rates. The results will be used to improve model predictions.

In the third year, model predictions of drill string measurements will be compared to kick events from industry. The well flow conditions of industry-supplied data, where actual kick events occur, will be modeled and the influx conditions varied to attempt to match the drill string measurements. Comparison of actual kick influx of specified fluids will be compared with the model predictions for accuracy and ability to obtain quantitation evaluation of kick fluid type and volume flow rates.

Research Products

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*Image Source: NETL

*Image Source: NETL


Janine Carney
Principal Investigator

Kelly Rose
Offshore Portfolio Lead

Roy Long
Offshore Portfolio Technical Manager
Effective Resource Development

Grant Bromhal
Senior Fellow
Geological & Environmental Systems

Philip Reppert
Associate Director
Geological & Environmental Systems

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