PUBLICATIONS
An original deconvolution approach for oil production allocation based on geochemical fingerprinting
November 2022
The paper presents an overview of the most widely employed techniques for production allocation. After highlighting the strength and drawbacks of each methodology, the Geolog approach is proposed. It consists of an improved experimental procedure for GC targeting production allocation and a novel deconvolution algorithm developed with Politecnico of Milan.
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geolog@geolog.it
Probabilistic assessment of equivalent fracture aperture constrained on quasi-real‑time drilling mud loss data
July 2022, Journal of Petroleum Exploration and Production Technology
Politecnico di Milano and Geolog Technologies developed an approach for the characterization of equivalent fracture apertures based on available mud loss information acquired in quasi-real-time while drilling.
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geolog@geolog.it
Integrated Formation Evaluation Using Multiple Geochemical Solutions to Optimize Reservoir Description and Evaluate Production Potential from Multiple Targets in the Northern Delaware Basin
June 2022, URTeC, URTeC: 3723283
This paper reports an integrated formation evaluation workflow on a multi-well case study in the Northern Delaware Basin using surface logging and laboratory analyses only. We will present how this approach provided subsurface characterization for enabling key drilling and completion decisions and optimizing future well planning and target selections
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geolog@geolog.it
Sensitivity Analysis and Quantification of the Role of Governing Transport Mechanisms and Parameters in a Gas Flow Model for Low-Permeability Porous Media
April 2022
The scope of the work is identifying a suitable model to represent gas (methane) migration in low-permeability media. This paper analyzed the relative importance of parameters driving gas flow in low-permeability formation. Employing statistical-based approaches, a simple, effective diffusion model embedding major methane flow mechanisms is derived.
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geolog@geolog.it
Predict Geomechanical Parameters with Machine Learning Combining Drilling Data and Gamma Ray
December, 2021, SPE Middle East Oil & Gas Show, SPE-204688-MS
The paper shows the development of a reliable method for geomechanical parameters evaluation while drilling using surface logging data. It combines ML drilling data, XRF and well log data with machine learning techniques. The paper shows that a model trained with drilling parameters and GR coming from one well can predict the Young Modulus of different wells (same basin)
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www.onepetro.org
Novel Approach to Reservoir Continuity Evaluation Through GC-MS Geochemical Fingerprinting
September 2021, 30th International Meeting on Organic Geochemistry, Online Meeting
Placido Franco PhD, Ivo Colombo PhD, Roberto Galimberti PhD,
GeoTech
Assessment of reservoir continuity through GC-fingerprinting is widely recognized to provide reliable results and has proven to be effective in supporting or replacing classical approaches such as those based on pressure data analysis. This paper reports an attempt to extend this reservoir geochemistry approach, normally applied to oil sample analysis, to the fingerprinting of cuttings extracts. Challenges, possible solutions and limitations of such an approach, as well as a case history are reported and discussed thoroughly.
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geolog@geolog.it
Carbon Isotopes from Mud Gas: Lab IRMS or Wellsite Laser-Assisted Technologies?
September 2019, 29th International Meeting on Organic Geochemistry (IMOG), Gothenburg, Sweden
Bianca Cecconi PhD and Roberto Galimberti PhD,
GeoTech
The objective of the study is to screen differences in carbon isotopic analysis between laboratory GC-IRMS and one of the possible alternative solutions for wellsite deployment, Cavity Ring-Down Spectroscopy (CRDS). Comparison examined advantages and disadvantages of two approaches and technical performances in terms of LoD, precision and accuracy.
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geolog@geolog.it
Quantification of Uncertainties of Fracture Permeability via Mud Loss Information and Inverse Stochastic Modeling
June 2019, 81st EAGE Annual Conference and Exhibition, London, UK
Alberto Guadagnini Prof., Anna Russian PhD, Monica Riva Prof., Politecnico di Milano, Eliana Russo MSc, Mario Chiaramonte MSc,
GeoTech
Fracture characterization of NFRs plays an important role in hydrocarbon production estimation. Uncertainty propagation from input parameters to model outputs is quantified through a Monte Carlo framework. Stochastic inverse modelling with field data is performed to evaluate posterior probability densities of fracture aperture and to simulate drilling fluid invasion in fractures in quasi-real time during drilling.
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geolog@geolog.it
H2S detection while drilling: a new approach
March 2019, 14th Offshore Mediterranean Conference and Exhibition, Ravenna, Italy
Luca Mascheroni MSc,
GeoTech
Oil and gas reserve contamination by acid gas is a growing issue and H2S occurrence is more and more frequent. The use of organic scavengers in drilling mud prevents the application of techniques routinely used for H2S detection. Geolog has set up an innovative methodology to highlight H2S distribution in reservoir, even in presence of these scavengers.
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geolog@geolog.it
High Resolution Geochemistry at Well Site, a New Emerging Tool
March 2019, AAPG Hedberg: The Evolution of Petroleum Systems Analysis: Changing of the Guard from Late Mature Experts to Peak Generating Staff, Houston, USA
Mario Chiaramonte MSc, Roberto Galimberti PhD,
GeoTech
The recent impressive improvements in analytical chemistry, due on one side to the growing needs of environmental monitoring and on the other to fast developments in nanotechnologies, made possible to move part of geochemical lab activities to wellsite. New portable and more robust instruments, able treplace bulky and complex instruments used in the labs, have been adopted in mud logging units, to introduce geochemistry at well site. This trend is still ongoing and other analytical techniques will be moved soon, offering new opportunities to get in quasi-real time additional high value data, matching lab quality standards.
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geolog@geolog.it
