PhD topic: Borehole electromagnetic modeling and inversion

I have a keen interest in modeling geophysical data. I graduated from Idea League joint master program in Applied Geophysics, which is held at TU Delft, ETH Zurich and RWTH Aachen, and I worked on electromagnetic induction inversion in my master thesis.

In this project, I will be working on borehole electromagnetic induction tool data inversion to provide the subsurface image around the borehole during the drilling process. I am going to study on implementation of finite difference and integral equation numerical method for fast and accurate forward modeling.

For the inversion, I will explore different parameterization and algorithm that can be used for stochastic inversion to quantify uncertainty. In addition, I am going to study the effect of anisotropy in the inversion. Data-driven method such as physics-based machine learning is also considered as one possible alternative for fast computation.

3D geological interpretation for geosteering of wells is a new knowledge building project for industry financed by the RCN Petromaks 2 program and the DigiWells’ industry partners.

The knowledge building project was evaluated very positively by international experts and awarded by RCN Petromaks in June.

In order to optimize well-placement decision support for drilling in complex formations, this work aims to establish and verify a workflow for automating, real-time, around-bit 3D geological interpretation of deep sensing electromagnetics(EM) logs. This workflow prepares the ground for future automatic updating of standard probabilistic 3D well-scale sector geomodels. The approach obviates the need for manual management of geomodels during the real-time phase.

Senior Researcher Nazanin Jahani, NORCE, will lead the project and collaboration partners will be University of Stavanger and UT Austin. NORCE and UiS have for many years benefitted from tight collaboration with prof. Reidar Bratvold, and in 2021 Jahani visited UT Austin for 5 months funded by a Fulbright scholarship. We are very happy to continue the fruitful collaboration with both UiS and UT Austin. The project will also benefit from a collaboration with Baker Hughes, that will contribute in-kind especially for the case studies. The active involvement of the supporting oil companies in DigiWells will ensure relevance of the project activities.

The geosteering activity in SFI DigiWells will be considerably strengthened by this project, and we are looking forward to starting the research.

The Fulbright Program is the U.S. government’s flagship international educational exchange program. It was created to increase mutual understanding between the peoples of the United States and other countries through the exchange of persons, knowledge, and skills. The Fulbright scolarship provides grants to individually designed research projects.

At the University of Texas at Austin, Jahani collaborated with the formation evaluation research consortium, which is managed by Professor Carlos Torres-Verdin. This consortium has more than 20 industry partners. The purpose of the research consortium’s program is to build knowledge for the industry.

On her Fulbright stay, Jahani worked with 3D numerical modeling of deep-sensing borehole resistivity measurements and petrophysical inversion. She focused on how electromagnetic measurements are used to evaluate the heterogeneity of formations. Likewise, she worked on numerical modelling of electromagnetic fields. Additionally, she got experience with implementing parallel algorithms in supercomputer clusters.

- My stay in the United States was useful, both personally and professionally, Jahani says.

Her passion is to apply mathematical modelling, computational methods, and numerical techniques to describe and represent the coupled physical processes, such as during drilling.

- On top of that, I love exploring and learning new things. My stay in the US opened me to new minds and cultures. I went through a uniquely shared history and knowledge with many people from diverse cultural and scientific backgrounds during my stay. I met several other Fulbrighters in Austin, and I established several long-term collaborations with other scientists at UT Austin as well as other Fulbrighters.

Nazanin Jahani has a PhD from 2015 in mechanical engineering. In addition, she has a master’s in computer software engineering. Since 2017 she has been a Research Scientist at NORCE.

- Now I will use the knowledge and continue the work in DigiWells, Jahani says.

New 3D technology for formation evaluation can contribute to better decisions during drilling and improved oil recovery.

- In my research, I will develop fast and robust 3D models and algorithms for formation evaluation, Jahani, says.

3D models are more accurate than lower-dimensional approximations and can provide much more detailed insight into the structure of the formation but are also very computationally intensive.

- My research aims to make these computations more efficient. The fast updated 3D models will contribute to optimizing decisions during the drilling operation and improve placement of the well. This may reduce costs due to avoidance of drilling problems, lower energy consumption and emissions and optimize the placement of the well resulting in improved oil recovery. Therefore, innovative technology may help the drilling crew and support team to make better decisions, Jahani says.

The ability to drill wells efficiently and safely in formations is essential in several contexts in addition to hydrocarbon extraction, like geothermal drilling, mining, and drilling of well for CO2 storage.

Ressi will work towards geosteering initiative.

Ressi Bonti Muhammad

PhD topic: Sequential decision analysis in drilling and geosteering

I come from Indonesia. My BSc is from Bandung Institute of Technology in Petroleum engineering. I recently graduated and earned my master’s degree from NTNU, also in Petroleum engineering.

Develop and improve a decision support system (DSS) that provides optimization-based decisions under geological uncertainty during drilling and geosteering. One of the main goals of the project is to include reinforcement learning (RL) for the DSS. Instead of building the model ourselves, we would like to develop a decision-maker/agent by training it directly on the environment, or in this case the drilling operation in the subsurface. The subsurface during a drilling operation remains uncertain, especially ahead of the bit. We try to reduce this uncertainty using the Bayes’ theorem and its discrete approximations: Ensemble Kalman Filter, particle filter, etc.

Today, NORCE Energy department has received a new SFI, DigiWells - Digital Well Centre for Value Creation, Competitiveness, and Minimum Environmental Footprint!

Keywords for the center:

• The cross-disciplinary and digitized work process for planning and execution of well delivery
• Benefit from new-generation sensors and digital technologies (digital twin, data assimilation, Machine Learning)
• Decision support systems for geosteering which balances well productivity and risk
• Automation and autonomous drilling operations
• Testing new solutions using the national research infrastructures Ullrigg and OpenLab Drilling

Research Partners

UiS, UiB, and NTNU will be the research partners participating in the project, as well as several other international universities outside of Norway.

Earlier this year we delivered the first noteworthy results which were featured in the SPE Journal of Petroleum Technology.

Geosteering for IOR: a competence-building for industry

Optimizing the recovery from petroleum reservoirs is crucial, and one significant factor is the directional steering of the drilling. Geosteering, the process of guiding drilling according to geological formations, relies on well-calibrated geological models and quantified uncertainties.

Current geosteering work processes have several shortcomings:

• Calibrating geomodels to deep Electromagnetic Measurements (EM) and Logging While Drilling (LWD) for complex formations is challenging.
• Current geomodels lack the flexibility for support of structural updates and fast local updates.
• There is an absence of a transparent, systematic, and consistent workflow for quantifying and incorporating geological uncertainties into geosteering decisions.

Project Objective

The primary goal is to develop a methodology for geosteering that involves continuously updating the geomodel based on LWD, including deep EM measurements. We are targeting these secondary objectives:

• Ensemble-based geosteering workflow: Creating an improved workflow that integrates with reservoir management.
• Processing deep EM measurements: Utilizing EM forward modelling tools and efficient processing of EM measurements.
• Flexible earth model representation: Developing a model that supports local updates and real-time uncertainty modelling.

Achievements

A prototype of an interactive Decision Support System (DSS) has been developed for synthetic cases, demonstrating optimal well placement in complex reservoir navigation scenarios. The findings were shared in the paper titled “An Interactive Decision Support System (DSS) for Geosteering Operations,” presented at the SPE Norway One Day Seminar on April 18th, 2018, and featured in the SPE Journal of Petroleum Technology in September 2018.

• Read the paper on OnePetro: “An Interactive Decision Support System for Geosteering Operations”​【oaicite:1】​.
• Featured in JPT: “New Geosteering Work Flow Integrates Real-Time Measurements With Geomodels”​【oaicite:0】​.