“Never run out of the Mud” – Drilling fluid automation

Problem statement

Well Construction fluid domain has a broad sphere of influence and interacts with all well-construction processes, including conventional drilling, well control, managed-pressure drilling, tripping, and running and cementing casing Because of this interdependence, which need to develop robust, automated equipment to measure critical fluid properties required by all these processes. lets explore how to build a automated system in the fluids and solids control domain and hence develop a vision, steps, approach and a possible solution.

Domain – Refresh

Drilling fluids are formulated to carry out a wide range of functions. Although the list is long and varied, key performance characteristics are the following:

Controlling formation pressures
Removing cuttings from the borehole
Cooling and lubricating the bit
Transmitting hydraulic energy to the bit and downhole tools
Maintaining wellbore stability

Broadly we can consider Drilling fluid design and maintenance are an iterative processes affected by surface and downhole conditions.
Initial design—In the planning phase, fluid experts select mud system types and designs for each borehole section.
Circulation—The drilling fluid’s character constantly evolves. In one circulation cycle, the fluid has expended energy, lifted cuttings, cooled the bit and hole and then released waste at the surface.
Measurement and redesign—The drilling fluids specialist measures certain properties of the returning mud.

Sucess Criteria

The future need for smart sensors

Ultimate success will depend not only on improved data from better measurements(sensors), but also comprehensive data management systems linked to interpretative schemes and predictive analyses that convert the data into actionable tasks, then learn from it which updates the knowledge, within Safety, health, environmental constraints, with the goal of efficiency improvements.The confluence of current drivers is moving the industry towards rig headcount reduction (for safety and economic reasons), and personnel removal from hazardous areas (for health reasons). However, there are others.Competency is of concern, due in part to the lack of skilled personnel to deliver a quality service at the rigsite without incurring increased non-productive time. Another is the transmission of relevant data to operational centers to have an integrated overview of the rigsite operation and to allow optimization of the total process, which also open multiwell commanding hub

Operational Efficiency:
NPT Reduction: Reduce human error by improving the workflow and usability
People Efficiency: Reduce crew size by remote operation

Vision (“Never run out of the Mud” – an Automated system)

Ensure consistent execution of manual and automated (supervised) well construction tasks by maintaining a high level of contextual understanding of the well, along with equipment states and the operational plan to adapt mud properties by optimizing solids control (with real-time measurements) to positively impact overall drilling performance

Steps to automate the operation

It is Interesting to see, if you analize wells(well construction process) on the same pad which, total days for completing drilling related actvities have high in variation, then you can see severe variation in the process of execution has been taken place for a same set of task. Define a consistant approach for executing a task (for a well construction process), within similar well condition(and constraints) is the key, and make sure those are following at the well site is very important. Automation systems are capable of doing this, please see my previous posts for details.

Lets lay out series of activities, which mud engineer and derrick hand does at the wellsite(time vs activity), from “Prepare rig to spud”, to Rig-up to prespud meeting to prepare fluid, to measure properties to prepare and perform treatment plan to displacement WBM to OBM …etc.

So where to start (automation) ?

Mud engineer ultimate goal at well site to improve drilling effeciency, by managing the fluid properties. Lets pick One activity which gives more value of mud engineer function is Optimizing treatments within operational planning limit to improve overall drilling performance. Lets take a look at the treatment complexity diagram. some of the key value for optimizing the treatments are below. Once treatment generation and management is digitized (and automated), that will initiate learning process, which will optimize (or redefine) the planning process for the future wells.

Minimize losses
Optimum treatments
Reinforce timely addition
Maximize solids control efficiency
Optimize dilution rate
Enable remote treatments
Revisit property spec for next well

Other than advanced sensors- such as inline accurate mud weight measurements, rheology measurements, solids, oil water ratio etc are required for understanding the current state of the system, components like automated closed loop pilot testing, better fluid mixing hardware etc are key for moving the system to a goal state within the constraints.

Technical considerations

Lets take a look at the high level architectural diagram

Are You Equipped, Technically and Culturally, to Run Event-Driven(Iot) Digital Business?

Lets evaluate architectural patterns to solve this problem, strength and weaknesses.

API-Driven model has its own strength and challenges
Strength

Direct control
Transaction integrity
Ubiquitous REST connectivity
API management and marketplaces
Data-as-a-Service APIs
Clients will include mobile apps and web dashboards
Real-time data and bulk data APIs

Consider your API Security Building Blocks

Quota management/Traffic throttling
Authentication of the API client
JSON/XML element encryption
Tokenization of sensitive information
Content inspection
Content validation(JSONschema, XML schema)
Automated attack/Bot detection
Transport security(TLS/SSL)
API key authentication
Store audit logs
Digital signature
Fine-grained authorization
OAuth scope management
Integration with access management
Alerting (including to SIEM)

Challenges

Direct one-to-one coupling
Requires synchronous access
Creates hierarchical dependencies
Stateful
Without API management, poorly instrumented for management

So lets Master Both APIs and Events to Design for Digital Business

Looks like in the industry, 92% of organizations found that IoT delivered more than expected outcomes

IOT workflows

Enhanced risk assessment for development of SLAs andwarranties
Address regulatory or compliance control need
Enhanced worker or visitor safety / health
Asset monitoring or optimization or sensor streaming(e.g. utilization, maintenance,etc.)
Workforce productivity enhancement
Remote monitoring and control of operations
Process improvement –business processes
Supply chain visibility, control, coordination, integrate (Mud engineer key functions)

External IoT benefit

Up-sell additional products or services
Automated replenishment of customers’ consumables
Ability to update/upgrade/unlock software for enhanced functionality
Migrate from selling products to selling Product-as-a-Service
Ability to remotely monitor faults (take decisions) and improve products or services
Gain greater insight into customer behavior (e.g., usage)
Satisfy regulatory requirements