Exploration, development, and production of oil and gas reserves are becoming increas-ingly difficult. The challenge is to access and produce the reserves in a cost-effective matter and maximizing the returns [45]. Digitalization and automation are of high inter-est, as it can lead to more consistent and efficient operations of higher quality [46]. Within the drilling industry operators are looking to reduce drilling costs by new and innovative technology with automation potential [45].
Carlsen et al. [47] proposed a method for directly measuring the frictional pressure loss associated with flow through pipe, instead of calculating it based on offline measurements of viscosity. The idea is to place differential pressure sensors at various locations in the standpipe and the pipes between the mud pumps and the standpipe. The results are used to estimate friction factors and the frictional pressure drop in a pipe of arbitrary length and diameter. The setup can be seen inFig. 10.1. During pipe connections, the valve at the top of the standpipe can be used to re-route the flow to a return line containing a choke. By circulating through this inner loop, compressibility, density, and frictional pressure loss can be computed at various pressures and flow rates. The process can be automated, by pre-programming a sequence of different pressures and flow rates to be applied. Simula-tions were performed to test the method and the results showed good indicaSimula-tions. There are some challenges with the method when it comes to the validity of using the computed estimates for fluid in a drillstring. Temperature effects on the fluid in the drillstring need to be accounted for. Rheology is affected by temperature changes, and the relationship is generally non-linear. In addition, drillstring inner diameter and pipe roughness might vary between different joints.
Taugbøl et al. [46] describe a similar system. It utilizes a pipe rheometer that measures differential pressure within a horizontal pipe section and within a vertical pipe section.
The data from the horizontal section contains information on the frictional pressure drop
Fig. 10.1– Instrumented standpipe set-up [47].
of the fluid running through the pipe. The data from the vertical section contains the same information, in addition to information about fluid density. Looking at this information to-gether with the fluid velocity, the rheology profile, and density of the drilling mud can be found. The shear rate dependent viscosity can also be found, by varying the fluid velocity.
Hydraulic models are utilized to compute density and viscosity. They take compressibil-ity, thermal effects, and pressure effects into consideration. Pressure and temperature at the rheometer measurements are recorded, and the hydraulic models correlate the rig site conditions to downhole conditions, to get accurate values for density and viscosity. The pipe rheometer is not a part of the standpipe, unlike the system described by Carlsen et al.
[47]. The rheometer has pipes of two different dimensions and an attached pump to variate the flow rate. It is also programmed to give data output of the same format given by tradi-tional viscometers. An offshore installation of the pipe rheometer can be seen inFig. 10.2.
Fig. 10.2– Offshore installation of pipe rheometer [46].
An operator has cooperated with various suppliers for years to develop and optimize tech-nology and equipment for automatic measurements of mud properties. It is important for systems to handle the challenging environments of drilling operations. The rheometer sys-tem was tested in a laboratory with real industry mud before it was implemented for an offshore field trial. The goal of the trials was to clear the system for company-wide im-plementation. Offshore installation required information about a suitable location for the rheometer and sampling point, as well as information about necessary cables and potential hot work [46].
The rheometer was able to monitor density and viscosity of the active volume during drilling and gave real-time data to both the operator and the vendor of the fluid. The system proved its value on several occasions during the drilling process. At one point the driller observed a decrease in pump pressure, which was assumed to be caused by drill pipe wash out. The mud engineer reviewed the data from the rheometer and pointed out that there also was a decrease in mud density and rheology. Due to this information, a small influx of water to the active volume was identified. The water influx was not detected by pit level alarms because the well was currently facing seepage loss [46].
There are several advantages of continuous measurement of density and viscosity. The
common manual measurements of viscosity are often performed with significant time in-tervals in between the measurements, and reactive treatments need to be initiated to return to the required mud properties. Considerate amounts of chemicals and dilutions can be saved by continuously measuring the rheology of the mud. It will also lead to more con-sistent mud properties, as unwanted changes are discovered and can be managed faster.
The previously mentioned operator had an incident in an offshore well, where no mud property measurements were taken between 21:00 and 05:00 the following morning. At 05:00 the viscosity values had increased severely, but the density had not changed. Drilling of a section containing reactive clay had taken place and contamination of the mud by the reactive clay was the cause of the increase in viscosity. Had the situation been discovered early enough, dilution of mud would have resolved the issue, but by the time it was dis-covered it was already too late and the whole active volume had to be replaced by new mud [46].
Due to positive results, it was decided that automatic measurements of density and vis-cosity would be implemented on all of the operator’s offshore installations in Norway. It is expected that the automatic measurements and hydraulic models will become standard equipment on most advanced offshore drilling installations. Further development is also expected for other parts of the drilling fluid system, for instance autonomous mud mixing and chemical treatments during drilling [46].
Bjørkevoll et al. [48] describe the use of an advanced hydraulic model for managed pres-sure drilling (MPD) utilized in the drilling of a well with very narrow prespres-sure margins in the North Sea. One of the formations had a narrow pressure window of approximately 7 bar. This was mainly due to high-pressure zones caused by injection wells in the area nearby. The desire was therefore to keep a constant BHP with a deviation within± 2.5 bar. To achieve this an automatically controlled choke and an automatically controlled back pressure pump were utilized, together with the hydraulic model. Input data to the hydraulic model used to calculate the target settings of the choke include drillstring pa-rameters, such as rotational speed, bit depth, string movement, and torque, as well as mud parameters measured at surface, such as flow rate, mud density, rheology, and temperature.
The surface measurements are correlated to downhole conditions using tables containing laboratory data.
Testing and tuning of the model were performed at the rig site before the start of the op-eration and during the opop-eration. Memory data were collected and reviewed to confirm that the BHP was kept constant when the MWD signals were not transmitted to surface, for instance during connections. The drilling operation was successfully completed and became the fifth MPD operation utilizing the advanced real-time model in the automated choke regulation loop with positive results. Normally in regulation loops, simpler models are used, but in MPD the challenges connected to tight and quickly shifting constraints can benefit from using a more advanced model, like the one described here [48].
Another automated MPD operation, that took place in Mexico East, is described by Ro-driguez et al. [49]. The well had issues with crossflow due to zones where losses occurred
combined with a steep pore pressure ramp. The associated mud weight window was nar-rower than 0.09 g/cm3. Previously there had been two failed attempts to reach the reser-voir. One of the attempts utilized automated MPD, but still resulted in a mud loss of over 1000 m3, a stuck pipe incident, and several well control situations.
A new automated MPD was planned with a mud density of 2.30 g/cm3 and a desired EMW 2.44 g/cm3throughout the section. For conventional drilling, a higher mud density would have been selected, but with MPD the surface back pressure will give the preferred downhole pressures. The use of back pressure pumps makes it easier to obtain stable pressure parameters, as well being a safety measure to cope with potential issues with the rig pumps, that could have resulted in a considerate drop in BHP. To handle the quickly shifting pressure conditions, controlled formation pressure tests were performed using the MPD choke. This helped to constantly identify the pressure window boundaries in an at-tempt to avoid severe losses and frequent well control situations. In addition, a Coriolis meter was included to rapidly detect loss or gain of fluids. Flow modeling was performed in the planning stage and used as initial input to the automated pressure control system.
Inputs entered to the model during drilling included updated surface back pressure and mud parameters [49].
The drilling operation was considered successful as the reservoir section was reached for the first time in the field. The automated MPD system identified abnormal pressures during drilling and responded quickly. Handling of the crossflow environment was improved and the number of well control events was reduced from 7 to 2 in comparison to the previous attempts. The hydraulic simulations performed ahead of the operation and the calcula-tions made by the automated WDP system coincided with real-time measurements made by logging tools during drilling, which resulted in higher confidence in the system. The new automated WDP system proved to be a good strategy for the challenges associated with the crossflow [49].
Chmela et al. [50] present a step-wise approach to automation. Despite the industry drive to develop new and innovative technology for drilling, parts of the industry can be considered conservative, especially when it comes to implementation of new solutions.
The move towards automatic systems replacing tasks previously performed by humans can therefore benefit from a step-wise approach. The first step presented consists of the rig crews performing ”engineering-while-drilling” calculations. This can either be in a passive mode to verify the automatic models or in an advisory mode to improve the models based on human experience. The second step is to utilize the calculations and boundaries found by the models. The third and final presented step is to allow the automation system to actively assist in the processes.