scholarly journals Visualization Research and Application of Uncertainty Method of Well Trajectory Based on ISCWSA Model

2021 ◽  
Vol 804 (2) ◽  
pp. 022060
Author(s):  
Hongyan Ma ◽  
Xiaoou Xu ◽  
Hongguo Xu ◽  
Xiaojian Song ◽  
Aibing Zhang ◽  
...  
2021 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Miguel Ángel Ruiz Reina

In this research, a new uncertainty method has been developed and applied to forecasting the hotel accommodation market. The simulation and training of Time Series data are from January 2001 to December 2018 in the Spanish case. The Log-log BeTSUF method estimated by GMM-HAC-Newey-West is considered as a contribution for measuring uncertainty vs. other prognostic models in the literature. The results of our model present better indicators of the RMSE and Ratio Theil’s for the predictive evaluation period of twelve months. Furthermore, the straightforward interpretation of the model and the high descriptive capacity of the model allow economic agents to make efficient decisions.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3011
Author(s):  
Yi Yang ◽  
Fei Li ◽  
Nan Zhang ◽  
Aiqing Huo

In the process of drilling, severe downhole vibration causes attitude measurement sensors to be erroneous; the errors will accumulate gradually during the inclination calculation. As a result, the ultimate well path could deviate away from the planned trajectory. In order to solve this problem, this paper utilized the stochastic resonance (SR) and chaos phase transition (CPT) produced by the second-order Duffing system to identify the frequency and estimate the parameters of the signal during measurement while drilling. Firstly, the idea of a variable-scale is introduced in order to reconstruct the frequency of the attitude measurement signal, and an SR frequency detection model based on a scale transformation Duffing system is established in order to meet the frequency limit condition of the SR. Then, an attitude measurement signal with a known frequency value is input into the Duffing chaos system, and the scale transformation is used again to make the frequency value meet the parameter requirement of chaos detection. Finally, two Duffing oscillators with different initial phases of their driving signal are combined in order to estimate the amplitude and phase parameters of the measurement signal by using their CPT characteristics. The results of the laboratory test and the field-drilling data demonstrated that the proposed algorithm has good immunity to the interference noise in the attitude measurement sensor, improving the solution accuracy of the inclination in a severe noise environment and thus ensuring the dynamic stability of the well trajectory.


2012 ◽  
Vol 524-527 ◽  
pp. 1232-1235 ◽  
Author(s):  
Li Feng Li ◽  
Xiang An Yue ◽  
Li Juan Zhang

Finding the breakthrough position of horizontal wells is essential to water plugging and improving oil production in bottom water drive reservoirs. Physical modeling was carried out in this paper to research the law of bottom water’s movement. The experimental results indicated that: pressure drop in wells, well trajectory and area reservoir heterogeneity were all sensitive factors for breakthrough of bottom water, and the entry points of horizontal wells were determined by the combined function of them. In different well trajectory models, the concave down part of the well cooperate with pressure drop influenced the breakthrough position. Bottom water below the heel end reached the well earliest if the concave down part located at the heel end. When the concave part located at the middle of the well, the two factors played role respectively which resulted in breaking through of bottom water at two places with larger swept area. In different heterogeneous models, permeability difference and pressure drop were both favorable factors for bottom water’s non-uniformly rise. In the model that the heel end located at high permeability part, bottom water under the heel end reached the well earliest. If the heel end was set at the low permeability part, the breakthrough of bottom water occurred at the middle of the well.


2021 ◽  
Author(s):  
Costeno Hugo ◽  
Kandasamy Rajeswary ◽  
Telles Jose ◽  
Camacho Jacob ◽  
Medina Diego ◽  
...  

Abstract Digital well construction tools are becoming more widely considered today for well design planning, enabling automated engineering and simultaneous team collaboration under a single solution. This paper shows the results of using a digital well construction planning solution during a project’s conceptual planning stage. This method shortens the time needed to estimate the well times and risk profile for a drilling campaign by applying smart engines to quickly and accurately perform critical offset analysis for defined well types that is required for project sanction. With this solution, the Offset Well Analysis (OWA) process is done automatically based on the location of the planned well, trajectory and well architecture. Various information and reports (both subsurface and surface data) from neighboring wells is stored in cloud solutions, enabling ease of access and data reliability for both large or smaller scale data storage. The software selects the most relevant offset wells, displays the risk analysis and generates the stick chart. For a conceptual design, the risk levels can be manually set higher due to potential unknowns in surface and subsurface risks which can later be refined. Quick validation of the well design allows the engineer to design a conceptual drilling campaign quickly and more efficiently. The solution minimizes the time to perform probabilistic time and risk estimations. It reduces the risk of biased decision making due to manual input and design. This allows for better-informed decisions on project feasibility, alignment of stakeholders, increased design reliability as well as reducing the amount of time and resources invested in OWA. The work presented here is aimed at sharing the experience of applying a digital well construction planning solution specifically on the conceptual project stage and discuss the value it adds to the well design process.


2021 ◽  
Author(s):  
Jon Gustav Vabø ◽  
Evan Thomas Delaney ◽  
Tom Savel ◽  
Norbert Dolle

Abstract This paper describes the transformational application of Artificial Intelligence (AI) in Equinor's annual well planning and maturation process. Well planning is a complex decision-making process, like many other processes in the industry. There are thousands of choices, conflicting business drivers, lots of uncertainty, and hidden bias. These complexities all add up, which makes good decision making very hard. In this application, AI has been used for automated and unbiased evaluation of the full solution space, with the objective to optimize the selection of drilling campaigns while taking into account complex issues such as anti-collision with existing wells, drilling hazards and trade-offs between cost, value and risk. Designing drillable well trajectories involves a sequence of decisions, which makes the process very suitable for AI algorithms. Different solver architectures, or algorithms, can be used to play this game. This is similar to how companies such as Google-owned DeepMind develop customized solvers for games such as Go and StarCraft. The chosen method is a Tree Search algorithm with an evolutionary layer on top, providing a good balance in terms of performance (i.e., speed) vs. exploration capability (i.e., it looks "wide" in the option space). The algorithm has been deployed in a full stack web-based application that allows users to follow an end-2-end workflow: from defining well trajectory design rules and constraints to running the AI engine and evaluating results to the optimization of multi-well drilling campaigns based on risk, value and cost objectives. The full-size paper describes different Norwegian Continental Shelf (NCS) use cases of this AI assisted well trajectory planning. Results to-date indicate significant CAPEX savings potential and step-change improvements in decision speed (months to days) compared to routine manual workflows. There are very limited real transformative examples of Artificial Intelligence in multi- disciplinary workflows. This paper therefore gives a unique insight how a combination of data science, domain expertise and end user feedback can lead to powerful and transformative AI solutions – implemented at scale within an existing organization.


2015 ◽  
Author(s):  
Vadim Tikhonov ◽  
Olga Bukashkina ◽  
Nikolay Abaltusov
Keyword(s):  

2021 ◽  
Author(s):  
Yaowen Liu ◽  
Wei Pang ◽  
Jincai Shen ◽  
Ying Mi

Abstract Fuling shale gas field is one of the most successful shale gas play in China. Production logging is one of the vital technologies to evaluate the shale gas contribution in different stages and different clusters. Production logging has been conducted in over 40 wells and most of the operations are successful and good results have been observed. Some previous studies have unveiled one or several wells production logging results in Fuling shale gas play. But production logging results show huge difference between different wells. In order to get better understanding of the results, a comprehensive overview is carried out. The effect of lithology layers, TOC (total organic content), porosity, brittle mineral content, well trajectory is analyzed. Results show that the production logging result is consistent with the geology understanding, and fractures in the favorable layers make more gas contribution. Rate contribution shows positive correlation with TOC, the higher the TOC, the greater the rate contribution per stage. For wells with higher TOC, the rate contribution difference per stage is relatively smaller, but for wells with lower TOC, it shows huge rate contribution variation, fracture stages with TOC lower than 2% contribute very little, and there exist one or several dominant fractures which contributes most gas rate. Porosity and brittle minerals also show positive effect on rate contribution. The gas rate contribution per fracture stage increases with the increase of porosity and brittle minerals. The gas contribution of the front half lateral and that of latter half lateral are relatively close for the "upward" or horizontal wells. However, for the "downward" wells, the latter half lateral contribute much more gas than the front half lateral. It is believed that the liquid loading in the toe parts reduced the gas contribution in the front half lateral. The overview research is important to get a compressive understanding of production logging and different fractures’ contribution in shale gas production. It is also useful to guide the design of horizontal laterals and fractures scenarios design.


2021 ◽  
Author(s):  
Michael Thiel ◽  
◽  
Haifeng Wang ◽  
Dzevat Omeragic ◽  
Jean-Michel Denichou ◽  
...  

Faulting is one type of structural trap for hydrocarbon reservoirs. With more and more fields moving toward the brownfield or mature operations stage of life, the opportunity to target bypassed or attic oil in the vicinity of bounding fault(s) is becoming more and more attractive to operators. However, without an effective logging-while-drilling (LWD) tool to locate and map a fault parallel to the well trajectory, it has been challenging and potentially high risk to optimally place a well to drain oil reserves near the fault. Operators often plan these horizontal wells at a significant distance away from the mapped fault position to avoid impacts to the well construction and production of the well. Often, the interpreted fault position, based on seismic data, can have significant lateral uncertainty, and uncertainties attached to standard well survey measurements make it challenging to place the well near the fault. This often results in the wells being placed much farther from the fault than expected, which is not optimal for maximizing recovery. In other cases, due to uncertainty in the location of the fault, the wells would accidentally penetrate the side faults and cause drilling and other issues. Conventional remote boundary detection LWD tools do not assist with locating the fault position, as they only detect formation boundaries above or below the trajectory and not to the side. In this paper, the authors propose a novel approach for mapping features like a fault parallel to the well trajectory, which was previously impossible to map accurately. This new approach utilizes a new class of deep directional resistivity measurements acquired by a reservoir mapping-while-drilling tool. The deep directional resistivity measurements are input to a newly devised inversion algorithm, resulting in high-resolution reservoir mapping on the transverse plane, which is perpendicular to the well path. These new measurements have a strong sensitivity to resistivity in contrast to the sides of the wellbore, making them suitable for side fault detection. The new inversion in the transverse plane is not limited to detecting a side fault; it can also map any feature on the transverse plane to the well path, which further broadens the application of this technology. Using the deep directional resistivity data acquired from a horizontal ultra-ERD well recently drilled in the Wandoo Field offshore Western Australia, the authors tested this approach against the well results and existing control wells. Excellent mapping of the main side fault up to 30 m to the side of the well was achieved with the new approach. Furthermore, the inversion reveals other interesting features like lateral formation thickness variations and the casing of a nearby well. In addition, the methodology of utilizing this new approach for guiding geosteering parallel to side fault in real time is elaborated, and the future applications are discussed.


2021 ◽  
Author(s):  
Chang Siong Ting ◽  
Nur’ain Minggu ◽  
Dahlila Kamat ◽  
Latief Riyanto ◽  
Chee Seong Tan ◽  
...  

Abstract Well B-2 is a dual-string producers with Distributed Temperature Sensing (DTS) fiber installed along the long string (i.e. Well B-2L) across the reservoir sections. Each zone comprises of sub-layers. This system enabled the operator to continuously monitor the wellbore temperature across all the producing intervals including gas-lift monitoring, well integrity identification, zonal inflow profiling and stimulation job evaluation. This paper mainly discusses the post matrix acid stimulation job with interpreted DTS and zonal Permanent Downhole Gauge (PDG) data. Well B-2L has been selected for matrix acidizing treatment to improve the productivity due to potential formation damage, proven by the declining production over the years. Prior to the execution of the acidizing job, several conformance jobs such as injectivity test, tubing pickling were performed. This is followed by the main acid treatment and flow back. DTS & zonal PDG data were acquired throughout the operation. A transient simulator model was built incorporating all the reservoir properties including well trajectory and completion schematic to analyze the DTS profile and understand the zonal inflow profiling for each zone post treatment. A baseline temperature was acquired for the geothermal evaluation. The DTS data has been studied according to actual event schedules. Some significant findings are; i) completion accessories effect (feedthru packers) creates temperature anomalies, ii) leak points detected at top producing zone signifies cooling effect due to injected fluid. The main treatment was intended at zone 2 and 3 using nitrified acid. However, leak points at top zone caused bypassed injection into Zone 1 and 2 instead. Fiber optic DTS warmback profiles post main-treatment was analyzed to quantify the fluid intake from sub-layer in each zone. Qualitatively from the DTS-interpreted zonal profiling, the data clearly shows most of treatment fluid is being injected into Zone 1 and 2 with no intakes at Zone 3. Furthermore, warmback analysis confirmed the high intake zones from sub-layers within the main zone based on the permeability contrast. This paper will further discuss the zonal injectivity understanding for improvement from the zonal-inflow profiling evaluation by incorporating DTS, PDG and surface production data.


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