Geology-Driven Drilling Parameter Control for High ROP Hole Cleaning
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Solution Overview
Problem
High drilling efficiency, measured by rate of penetration (ROP), often leads to inadequate hole cleaning due to excessive cuttings production, resulting in stuck pipe incidents and non-productive time (NPT), increasing operational costs and drilling time.
Innovation Solution
A method and system that utilize historical data from wells with high ROP to train models for optimizing drilling parameters such as weight on bit, flow rate, and rotational speed, while minimizing NPT by selecting and aligning historical wells with similar conditions and adjusting control setpoints in real-time to maintain optimal drilling practices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high rate of penetration (ROP) is used to increase drilling efficiency, then drilling speed is improved, but cuttings production increases leading to inadequate hole cleaning and stuck pipe incidents
Solution Approach 1:
The system dynamically adjusts drilling parameters (weight on bit, rotational speed, flow rate) in real-time based on feedback from sensors monitoring cuttings concentration and hole cleaning conditions. This allows the drilling operation to maintain high ROP when conditions permit while automatically reducing parameters to prevent stuck pipe when cuttings accumulation becomes excessive
Solution Approach 2:
The system implements a closed-loop control mechanism where sensors continuously monitor drilling conditions including cuttings concentration, hydraulic pressure, and flow rate. This feedback is processed by the control system which adjusts drilling parameters accordingly, enabling the system to respond to changing conditions and maintain optimal balance between ROP and hole cleaning effectiveness
2Productivity
If high rate of penetration (ROP) is used to reduce drilling time, then productivity is improved, but non-productive time (NPT) increases due to stuck pipe incidents
Solution Approach 1:
The system proactively monitors drilling conditions and adjusts parameters before stuck pipe incidents occur. By detecting early signs of cuttings accumulation and hydraulic inefficiency, the system preemptively reduces weight on bit or increases flow rate to prevent stuck pipe conditions, thereby avoiding NPT entirely rather than responding after the problem occurs
Solution Approach 2:
The drilling system transitions from static parameter settings to dynamic real-time adjustment, allowing continuous optimization of ROP while maintaining hole cleaning effectiveness. This dynamic control enables the system to adapt to changing geological conditions and prevent NPT events while maximizing overall drilling productivity
3Productivity
If high rate of penetration (ROP) is used to enhance drilling efficiency, then operational cost is reduced, but stuck pipe incidents increase leading to additional operations and costs
Solution Approach 1:
The system uses real-time feedback from sensors monitoring cuttings concentration, hydraulic pressure, and flow rate to continuously adjust drilling parameters. This feedback mechanism prevents stuck pipe incidents by detecting early warning signs and automatically adjusting parameters to maintain optimal hole cleaning, thereby avoiding the additional costs associated with stuck pipe remediation operations
Solution Approach 2:
The drilling system performs self-adjustment of parameters to maintain optimal operating conditions. The control system automatically responds to changing conditions by adjusting weight on bit, rotational speed, and flow rate without requiring manual intervention, thereby preventing stuck pipe incidents and reducing operational costs through autonomous optimization
Data Source
AI summary
A method of drilling includes obtaining historical data for historical wells in a field, determining a set of drilling parameters, and determining a set of hole section sizes defining a wellbore geometry. For each combination of a parameter in the set of parameters and a hole section size in the set of hole section sizes, historical wells having average values of the parameter exceeding a threshold for the hole section size from the historical surface drilling data are selected. An expected output for each of a model to be trained by each of the selected historical wells is derived based on a rate of penetration while drilling. A final model is trained with the selected historical wells and expected outputs. An operating envelope is determined for each of the parameters in the set of parameters from the trained model. The operating envelopes may be used to guide drilling of a well in the field.