Formation Evaluation From Logging on Cuttings

1998 ◽  
Vol 1 (03) ◽  
pp. 238-244 ◽  
Author(s):  
F.J. Santarelli ◽  
A.F. Marsala ◽  
M. Brignoli ◽  
E. Rossi ◽  
N. Bona

Abstract This paper presents an overview of a vast research project named Formation Evaluation 2000 that was undertaken by Agip SpA and was aimed at characterizing in real time the formations encountered during drilling by the mean of measurements on drill chips. To date, the project has demonstrated the feasibility to obtain representative values of the P and S wave velocities, rock strength and deformability, permeability, porosity, density, residual fluid content and saturation. Further work is underway in order to gain access to the pore size distribution, the thermal expansion and the conductivity of the rocks. The paper presents the methodology used systematically to assess such a feasibility and illustrates the results obtained to date during the various sequences of the research - i.e. primary design of the measure, laboratory tuning and field applicability. Furthermore, a series of field cases where these techniques were used are presented in order to highlight the industrial applications of such a package of measurements. Introduction In the oil industry, Formation Evaluation is traditionally performed after the drilling of the well by a series of techniques amongst which one can mention:core measurements which give direct indications but which are necessarily limited in space as it is often uneconomical to core continuously all the formations of interest;logs which give continuous measurements but which are often indirect - e.g. porosity from sonic logs;well tests of whatever nature - e.g. may they be for permeability determination or fracturation pressure, etc. - and which give large scale information about the rocks.In practice, the main drawback of such techniques is not so much technical than temporal in so far as they allow the characterization of the formations only after the end of the well whilst a while drilling evaluation would benefit many operations. For this reason, the industry has developed the Measurement While Drilling (MWD) and Logging While Drilling (LWD) techniques which aim at obtaining a real time formation evaluation. These techniques consist in inserting high technology sensors in the Bottom Hole Assembly and at performing and recording various measures on the formations soon after they have been discovered by the bit. Nevertheless, such techniques also suffer from various drawbacks which are listed below in a non-exhaustive manner: i. in the case when the measurement is sent directly from the bottom of the hole to the rig floor, the lag time for the availability of the information is only due to the distance between the bit and the sensor which may be several hours if the instantaneous Rate Of Penetration (ROP) is slow - e.g. < 2 m/h -; ii. in the case when the measurement is not sent to surface, the information only becomes available once the bit is pulled out of hole which may mean several days after the formations have been uncovered by the bit; iii. MWD and LWD tools are expensive high technology equipments which require a high degree of well stability to be run such as to minimize the risk of leaving them downhole because of a stick pipe problem. iv. finally, the interpretation of the measurements may be quite complicated as corrections have to be brought for various factors such as for example the vibrations of the drillstring in the case of the Sonic While Drilling. Because of the global situation described above, Agip decided to investigate the possible use of cuttings to perform quantitative physical determinations of the properties of the formations encountered by the well. As questions about the physical representativity of cuttings were raised very early in the project, it was decided to follow a two stage approach:

2021 ◽  
Author(s):  
Victor Imomoh ◽  
Kenneth Amadi ◽  
Johnbosco Onyeji

Abstract The most common challenge in horizontal drilling is depth uncertainty which can be due to poor seismic data or interpretation. It is arguable that a successful landing of the wellbore in the reservoir optimally and within the desired zone is the most challenging in most geosteering operation. The presence of fluid contacts such as oil-water-contact (OWC) and gas-oil-contact (GOC) complicates the whole drilling process, most especially if these fluid contacts are not well defined or known. Additionally, the ability to map the boundaries of the reservoir as the BHA drills the lateral section is an added advantage to remaining within the desired reservoir section. The success of any reservoir navigation service where seismic uncertainty at the reservoir top is high will rely largely on how effective the geosteering system is and how the geosteering engineer is able to react promptly to changes while landing the well in the reservoir and drilling the lateral section with without exiting the reservoir. Reservoir Navigation Service (RNS) provides the means for the drilling near horizontal or horizontal wells for the purpose of increasing hydrocarbon extraction from the earth's subsurface. This involves the use of a pre-defined bottom hole assembly (BHA) with inbuilt downhole logging while drilling (LWD) and measurement while drilling (MWD) sensors. The measurements from these downhole sensors are uplinked to the surface of the wellbore where they are converted to meaningful petrophysical data. The goal is to use the downhole petrophysical data such as gamma ray, propagation resistivity and so on, to update an existing pre-well geological model of a section of the earth in such a way that the final result depicts the true model picture of the earth subsurface. This paper focuses on using well CBH-44L to showcase how the use of real-time distance-to-boundary (D2B) measurement from a deep reading azimuthal propagation resistivity tool is use to correct for depth uncertainty in seismic, thereby, improving the chance of successfully landing and drilling a horizontal well.


2021 ◽  
Author(s):  
Mahmoud ElGizawy ◽  
Knut Ness ◽  
Saleel Kolakkodan

Abstract Wellbore surveying is critical while drilling in order to assure the drilled well is following the plan and is penetrating the geological target. Additionally, wellbore surveying is the key to allowing a well to be drilled safely, avoiding other wells drilled in the same field, and optimizing reservoir production. Standard wellbore surveying accuracy is increasingly inadequate for optimizing the well placement in real time to maximize the reservoir recovery due to maturity of the field. The other disadvantage of the standard wellbore surveying often requires running an additional wellbore surveying tool to improve the accuracy in order to manage the collision avoidance with nearby wells in the same field, introducing unwanted time and costs. Hence, this article presents the advanced wellbore surveying technology that is successfully implemented in offshore fields of Abu Dhabi to overcome the limitations of the standard surveying accuracy without compromising rig time. Magnetic measurement while drilling (MWD) surveys are common standard and utilized in every directional well in this operation. To overcome the standard accuracy limitation, advanced survey correction to the magnetic MWD surveys is introduced. This includes in-field referencing to provide a higher resolution magnetic reference to calculate a more accurate well direction, correction to the effect of the steel components in the bottom hole assembly on the magnetic MWD surveys, correction to the errors associated with survey sensors calibration, and correction to any misalignment between the survey tool and the wellbore. Correcting the surveys in real-time while drilling is the key to placing the well accurately and to avoid offset wells in the close proximity. The details of the corrections methodology are discussed. Advanced magnetic survey correction procedures in real-time are outlined and mapped out. Finally, results of improving the magnetic surveys while drilling in placing the wells and minimizing the collision risk of offset wells are presented. This advanced survey technology allows drilling previously un-drillable wells in these offshore fields, and the allowance for increased density of wells in the reservoir gives the operator opportunity to maximize production recovery and extend the life of reservoir. Higher accuracy of wellbore surveys is an increasing requirement in mature fields to safely allow more accurately placed wellbores with the required production rates. This allows for improved well placement along the trajectory facilitating adjustment at control points and landing points to maximize the hydrocarbon production. In addition, it allows controlling the probability of collision with any nearby wells. The enhanced wellbore surveying accuracy is achieved by advanced magnetic survey corrections in real time. This is controlled by a stringent novel process and communication protocol in order to meet the accuracy objectives.


2018 ◽  
Vol 68 (12) ◽  
pp. 2857-2859
Author(s):  
Cristina Mihaela Ghiciuc ◽  
Andreea Silvana Szalontay ◽  
Luminita Radulescu ◽  
Sebastian Cozma ◽  
Catalina Elena Lupusoru ◽  
...  

There is an increasing interest in the analysis of salivary biomarkers for medical practice. The objective of this article was to identify the specificity and sensitivity of quantification methods used in biosensors or portable devices for the determination of salivary cortisol and salivary a-amylase. There are no biosensors and portable devices for salivary amylase and cortisol that are used on a large scale in clinical studies. These devices would be useful in assessing more real-time psychological research in the future.


2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.


Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.


2021 ◽  
Vol 77 (2) ◽  
pp. 98-108
Author(s):  
R. M. Churchill ◽  
C. S. Chang ◽  
J. Choi ◽  
J. Wong ◽  
S. Klasky ◽  
...  

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