Vertical to Horizontal - Ultra Deep Azimuthal Resistivity Tool UDAR Service Helping to Maximize Production

2021 ◽  
Author(s):  
Ahmed Zarroug El Sedeq ◽  
Neal Hughes ◽  
Tore Oian ◽  
Piotr Byrski ◽  
Jean-Michel Denichou ◽  
...  
Keyword(s):  
Real Time ◽  
Horizontal Well ◽  
Optimal Placement ◽  
Temperature Management ◽  
Trajectory Design ◽  
Time Inversion ◽  
Reservoir Properties ◽  
Gas Field ◽  
Well Design ◽  
Azimuthal Resistivity

Abstract Dvalin field, discovered in 2010-2012. The location of this field is in the Norwegian Sea, as shown in (Figure 1). Dvalin field is an HPHT gas field in Middle Jurassic sandstone in the Garn and Ile Formations – the former being homogeneous with better reservoir properties, during the later heterogenous with low quality. (DVALIN, 2020) The well 6507/7-Z-2 H objective is to produce hydrocarbons from the Jurassic reservoir section of the Dvalin field safely and cost-effectively. The well was planned to be drilled near vertical in the reservoir section and TD'ed at a maximum depth corresponding to the Garn Formation base. After the productivity results from Z-3-H well came in at the low end of expectations, it was evaluated and decided to change the well profile of the Z-2-H well from vertical reservoir penetration to a horizontal profile; to have two penetrations with a minimum of 150m MD separation in the upper high permeable streak and then drop to penetrate lower high permeable streak. This decision was conducted only three days before starting the 17.5-inch section on the subject well. One Team culture was the key to achieving this significant change successfully. The decision to change the well-profile was conducted after a thorough engineering evaluation, including offset well analysis, which was very limited as the closest horizontal well was more than 40 km away. As the well was not planned as a horizontal well, departure between the surface location and Target Easting & Northing was minimal. Therefore, a high turn and deeper inclination build were required, which added some complexity to the well design. One of the additional primary risks related to this change of trajectory design is deploying a more complex BHA design in the reservoir section with a full suite of LWD technologies run in an HT environment. In the planning phase, special consideration was needed to accurately simulate the expected circulating temperature and have proper procedures in place for temperature management and control. Being the first horizontal well in the field, thus detailed planning was key for successful execution. Ultra-Deep Azimuthal Resistivity Tool (UDAR) Reservoir-Mapping capability was considered to help optimize the landing and navigate within the reservoir section. A feasibility study was conducted, and a 2-receiver Ultra Deep Azimuthal Resistivity Tool BHA configuration was selected and deployed. During the execution, the Ultra Deep Azimuthal Resistivity Tool real-time inversion mapped the reservoir geometry, revealing resistive layers within the Garn formation, thereby facilitating optimal placement of the well to achieve the set objectives. The well execution was largely considered flawless, with the real-time Ultra Deep Azimuthal Resistivity Tool data and corresponding interpretations facilitating decisions.

INTEGRATION OF RESERVOIR AND WELL FLOW SIMULATORS FOR ANALYSIS OF HORIZONTAL WELL PERFORMANCE

2007 ◽  
Vol 47 (1) ◽  
pp. 181
Author(s):  
G. Sanchez ◽  
A. Kabir ◽  
E. Nakagawa ◽  
Y. Manolas
Keyword(s):  
Real Time ◽  
Horizontal Well ◽  
Pressure Profile ◽  
Learning System ◽  
Well Performance ◽  
Reservoir Properties ◽  
Well Completion ◽  
Real Time Analysis ◽  
Reservoir Simulator ◽  
Inflow Performance

The optimisation of a well’s performance along its life cycle demands improved understanding of processes occurring in the reservoir, near wellbore and inside the well and flow lines. With this purpose, the industry has been conducting, for several years, initiatives towards reservoirwellbore coupled simulations.This paper proposes a simple way to couple the near wellbore reservoir and the wellbore hydraulics models, which contributes to the optimisation of well completion design (before and while drilling the well) and the maximisation of the well inflow performance during production phases, with support of real-time and historical data. The ultimate goal is the development of an adaptive (self-learning) system capable of integrated, real-time analysis, decision support and control of the wells to maximise productivity and recovery factors at reservoir/field level. At the present stage, the system simulates the inflow performance based on an iterative algorithm. The algorithm links a reservoir simulator to a hydraulics simulator that describes the flow inside the wellbore. The link between both simulators is based on equalisation of flow rates and pressures so that a hydraulic balance solution of well inflow is obtained. This approach allows for full simulation of the reservoir, taking into consideration the petrophysical and reservoir properties, which is then matched with the full pressure profile along the wellbore. This process requires relatively small CPU time and provides very accurate solutions. Finally, the paper presents an application of the system for the design of a horizontal well in terms of inflow profile and oil production when the production is hydraulically balanced.

scholarly journals Optimization of Horizontal Well Direction and Length Considering Geomechanics Properties and Drainage Area Using Genetic Algorithm in A Gas Field

2017 ◽  
Vol 11 (9) ◽  
pp. 114
Author(s):  
Prasandi Abdul Aziz ◽  
Tutuka Ariadji
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Horizontal Well ◽  
Random Search ◽  
Gas Production ◽  
Production Performance ◽  
Drainage Area ◽  
Trial And Error ◽  
Reservoir Properties ◽  
Gas Field

To maximize a horizontal well production, we need to determine the optimum direction and horizontal well length that maximizes the gas field recovery for a certain constant flow rate called by plateau rate. This problem is conventionally solved by using a reservoir simulation model and trial and error procedure that consumes considerably a lot of time and efforts. This study uses a random search method, i.e., Genetic Algorithm (GA), to solve this optimization problem and it very much eases to find the best well location with less time and efforts consumed.Along the general technique in directing a horizontal well towards the least principal stress of rocks, this study considers the geomechanics effects that influence the gas production performance. And also, the drainage area of horizontal well will be considered in this study to obtain the optimum horizontal well direction and length. In order to do this, a new proposed objective function for the GA has been constructed based on basic reservoir properties (i.e., porosity, permeability and gas saturation) and geomechanics properties (i.e., Young’s modulus and Poisson’s ratio). The results of the proposed method are validated using a reservoir model and economics evaluation.It may be concluded that the applying GA, with the appropriate objective function, can give accurate and faster results compared with the trial and error method using reservoir simulator, technically and economically, and also the proposed method is able to reduce the amount of works considerably time.

Horizontal Well Penetration Rate Increasing Technology in Sulige Gas Field

2015 ◽  
Vol 733 ◽  
pp. 17-22
Author(s):  
Yang Liu ◽  
Zhuo Pu He ◽  
Qi Ma ◽  
Yu Hang Yu
Keyword(s):  
Horizontal Well ◽  
Economies Of Scale ◽  
Reference Value ◽  
Drilling Speed ◽  
Underground Engineering ◽  
Gas Field ◽  
Horizontal Section ◽  
Well Drilling ◽  
Drilling Parameters ◽  
Key Techniques

In order to improve the drilling speed, lower the costs of development and solve the challenge of economies of scale development in sulige gas field, the key techniques research on long horizontal section of horizontal well drilling speed are carried out. Through analyzing the well drilling and geological data in study area, and supplemented by the feedback of measured bottom hole parameters provided by underground engineering parameters measuring instrument, the key factors restricting the drilling speed are found out and finally developed a series of optimum fast drilling technologies of horizontal wells, including exploitation geology engineering technique, strengthen the control of wellbore trajectory, optimize the design of the drill bit and BHA and intensify the drilling parameters. These technologies have a high reference value to improve the ROP of horizontal well in sulige gas field.

A Novel Workflow for Geosteering a Horizontal Well in a Low Resistivity Contrast Anisotropic Environment: A Case Study in Semoga Field, Indonesia

2021 ◽  
Author(s):  
Yessica Fransisca ◽  
Karinka Adiandra ◽  
Vinda Manurung ◽  
Laila Warkhaida ◽  
M. Aidil Arham ◽  
...  
Keyword(s):  
Real Time ◽  
Horizontal Well ◽  
Gamma Ray ◽  
Lessons Learned ◽  
Electrical Anisotropy ◽  
Anisotropy Ratio ◽  
Well Placement ◽  
Low Contrast ◽  
Low Resistivity ◽  
The Subject

Abstract This paper describes the combination of strategies deployed to optimize horizontal well placement in a 40 ft thick isotropic sand with very low resistivity contrast compared to an underlying anisotropic shale in Semoga field. These strategies were developed due to previously unsuccessful attempts to drill a horizontal well with multiple side-tracks that was finally drilled and completed as a high-inclined well. To maximize reservoir contact of the subject horizontal well, a new methodology on well placement was developed by applying lessons learned, taking into account the additional challenges within this well. The first approach was to conduct a thorough analysis on the previous inclined well to evaluate each formation layer’s anisotropy ratio to be used in an effective geosteering model that could better simulate the real time environment. Correct selections of geosteering tools based on comprehensive pre-well modelling was considered to ensure on-target landing section to facilitate an effective lateral section. A comprehensive geosteering pre-well model was constructed to guide real-time operations. In the subject horizontal well, landing strategy was analysed in four stages of anisotropy ratio. The lateral section strategy focused on how to cater for the expected fault and maintain the trajectory to maximize reservoir exposure. Execution of the geosteering operations resulted in 100% reservoir contact. By monitoring the behaviour of shale anisotropy ratio from resistivity measurements and gamma ray at-bit data while drilling, the subject well was precisely landed at 11.5 ft TVD below the top of target sand. In the lateral section, wellbore trajectory intersected two faults exhibiting greater associated throw compared to the seismic estimate. Resistivity geo-signal and azimuthal resistivity responses were used to maintain the wellbore attitude inside the target reservoir. In this case history well with a low resistivity contrast environment, this methodology successfully enabled efficient operations to land the well precisely at the target with minimum borehole tortuosity. This was achieved by reducing geological uncertainty due to anomalous resistivity data responding to shale electrical anisotropy. Recognition of these electromagnetic resistivity values also played an important role in identifying the overlain anisotropic shale layer, hence avoiding reservoir exit. This workflow also helped in benchmarking future horizontal well placement operations in Semoga Field. Technical Categories: Geosteering and Well Placement, Reservoir Engineering, Low resistivity Low Contrast Reservoir Evaluation, Real-Time Operations, Case Studies

Implementation of Vendor-Independent Stochastic Inversion for Improving Quality and Efficiency of Well Placement on the Field of Novatek Company

2021 ◽  
Author(s):  
Danil Andreevich Nemushchenko ◽  
Pavel Vladimirovich Shpakov ◽  
Petr Valerievich Bybin ◽  
Kirill Viktorovich Ronzhin ◽  
Mikhail Vladimirovich Sviridov
Keyword(s):  
Real Time ◽  
Well Placement ◽  
Stochastic Inversion ◽  
Mathematical Algorithm ◽  
Service Companies ◽  
Resistivity Data ◽  
Resistivity Logging ◽  
Azimuthal Resistivity ◽  
Logging Tool ◽  
Single Approach

Abstract The article describes the application of a new stochastic inversion of the deep-azimuthal resistivity data, independent from the tool vendor. The new model was performed on the data from several wells of the PAO «Novatek», that were drilled using deep-azimuthal resistivity tools of two service companies represented in the global oilfield services market. This technology allows to respond in a timely manner when the well approaches the boundaries with contrasting resistivity properties and to avoid exit to unproductive zones. Nowadays, the azimuthal resistivity data is the method with the highest penetration depth for the geosteering in real time. Stochastic inversion is a special mathematical algorithm based on the statistical Monte Carlo method to process the readings of resistivity while drilling in real time and provide a geoelectrical model for making informed decisions when placing horizontal and deviated wells. Until recently, there was no unified approach to calculate stochastic inversion, which allows to perform calculations for various tools. Deep-azimuthal resistivity logging tool vendors have developed their own approaches. This article presents a method for calculating stochastic inversion. This approach was never applied for this kind of azimuthal resistivity data. Additionally, it does not depend on the tool vendor, therefore, allows to compare the data from various tools using a single approach.

Advanced Horizontal Well Correlation Method for Dynamic Update of Subsurface Layers While Geosteering

2021 ◽  
Author(s):  
Abdul Mohsen Al-Maskeen ◽  
Sadaqat Ali
Keyword(s):  
Real Time ◽  
Horizontal Well ◽  
Control Point ◽  
Correlation Method ◽  
Thickness Variation ◽  
Structural Framework ◽  
Framework Model ◽  
Subsurface Layers ◽  
The Creation ◽  
Well Correlation

Abstract A new automated approach to well correlation is presented that utilizes real-time Logging While-Drilling (LWD) data and predicted well curve to dynamically update subsurface layers during geosteering operations. The automatically created predicted log and a dynamically updated structural framework provides the foundation of the process. The predicted log is created using vertical sections of the nearby wells, which provide high confidence for determining depth and stratigraphic position of the geosteered well. The results give a better understanding of thickness variation in the horizontal part of the reservoir and maximize the reservoir contact (Sung, 2008). A new advanced methodology introduced in this study involves the creation of a dynamic structural framework model, from which horizontal well correlation is performed using real-time well logs and predicted logs that are generated from adjacent wells. The predicted logs are correlated to the LWD logs using anchor points and an interactive stretching and squeezing process that honors true stratigraphic thickness. Each new anchor point results in the creation of an additional control point that is used to build a more precise structural framework model. This new approach enables more rapid well log interpretation, increased accuracy and the ability to dynamically update the subsurface model during drilling. It also enables more efficient steering of the wellbore into the most productive zones of the reservoir. This study demonstrates how wells with over 10,000 feet of horizontal reservoir contact can be correlated in a real-time geosteering environment in a dynamic, efficient and accurate manner. The proposed process dramatically helps reduce the cost of drilling and the time it takes to dynamically regenerate accurate updated maps of the subsurface. It represents a major improvement in the understanding and modeling of complex, heterogeneous reservoirs by fostering a multi-disciplinary environment of cross-domain experts that are able to collaborate seamlessly as asset-teams. Both accuracy and efficiency gains have been realized by incorporating this methodology in the characterization of multi-stacked reservoirs.

Real-Time Simulation of Deep Azimuthal Resistivity Tool in 2D Fault Model Using Neural Networks

2018 ◽  
Author(s):  
Dmitry Kushnir ◽  
Nikolay Velker ◽  
Alexey Bondarenko ◽  
Gleb Dyatlov ◽  
Yuliy Dashevsky
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Fault Model ◽  
Real Time Simulation ◽  
Time Simulation ◽  
Azimuthal Resistivity
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