Slim LWD Spectral Gamma Ray for Both Well Placement and Petrophysical Evaluation of Clastic Reservoirs in Saudi Arabia

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

10.2118/204547-ms ◽

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

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Characteristics of Paleozoic tight gas sandstone reservoir: integration of lithofacies, paleoenvironments, and spectral gamma-ray analyses, Rub’ al Khali Basin, Saudi Arabia

Arabian Journal of Geosciences ◽

10.1007/s12517-019-4467-0 ◽

2019 ◽

Vol 12 (11) ◽

Cited By ~ 2

Author(s):

Abdullah Alqubalee ◽

Osman Abdullatif ◽

Lameed Babalola ◽

Mohammad Makkawi

Keyword(s):

Saudi Arabia ◽

Gamma Ray ◽

Tight Gas ◽

Sandstone Reservoir ◽

Tight Gas Sandstone

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APPLICATIONS OF SPECTROLITH MINERALOGY FROM NEUTRON CAPTURE SPECTROSCOPY TOOLS FOR FORMATION EVALUATION

The APPEA Journal ◽

10.1071/aj02029 ◽

2003 ◽

Vol 43 (1) ◽

pp. 555

Author(s):

Z.J. Pallikathekathil ◽

M. Wilson

Keyword(s):

Neutron Capture ◽

Gamma Ray ◽

Accurate Estimate ◽

Light Hydrocarbon ◽

Gas Wells ◽

Matrix Density ◽

The Matrix ◽

Oxygen Ratio ◽

Weight Proportion ◽

Petrophysical Evaluation

When performing a petrophysical analysis, an accurate understanding of the mineralogy of the formations of interest is important for two main reasons. Firstly, the mineralogy of the formations controls the matrix density, which is fundamental in the evaluation of porosity using conventional methods. Secondly, an accurate estimate of the fraction of clay minerals present in the formation is essential in accurately correcting resistivity-based saturation estimates for the effects of excess clay conductivity.Accurately evaluating the mineralogy in formations containing both gas and radioactive minerals such as feldspars can be a challenge. Traditional clay indicators such as gamma ray estimate clay volumes which are too high due to the radioactivity coming from matrix grains such as potassium feldspars, feldspar rich volcanolithic grains and muscovite. In formations having light hydrocarbon such as gas or condensate, density-neutron logs under-estimate the volume of clays due to the light hydrocarbon effects on the density and neutron logs. Moreover, if the logs are to be acquired in a borehole with gas, air or foam, only a limited number of tools sensitive to mineralogy may be run. Using the SpectroLith technique, data from neutron capture spectroscopy tools such as the Reservoir Saturation Tool (RST) or Elemental Capture Spectroscopy Sonde (ECS) can be used to provide answers in these challenging situations.The RST is normally logged in cased hole for the sigma or carbon/oxygen ratio logs useful for determining formation saturation. The SpectroLith processing extracts lithology information, and in turn the weight proportion of clay, quartz-feldspar-mica, carbonate, pyrite, anhydrite and coal. The ECS tool is optimised for providing SpectroLith results at faster logging speeds in larger boreholes.This paper demonstrates, through examples from Australia, the applications of SpectroLith results derived from RST and ECS measurements. Two examples with the RST and one with the ECS are presented. In one example, the only available source of mineralogical information was from the results of SpectroLith processing applied to RST data. The second example shows how SpectroLith results can complement a through casing petrophysical evaluation. The example using ECS compares the mineralogy from a traditional analysis with that from SpectroLith processing and demonstrates the improvements to the petrophysical evaluation through a more accurate mineralogical description. Although no complete examples are available in gas wells in Australia at present, SpectroLith provides a promising way for accurately estimating mineralogy in gas wells.

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Linking Sequence Stratigraphy, Depositional Environment And Sedimentary Facies To Model The Sandstone 3D Architecture Within Palaeozoic Clastic Reservoirs, Saudi Arabia

10.2118/113733-ms ◽

2008 ◽

Author(s):

Ahmad Nazhri Bin Mohd Zain ◽

Mohammad Ahamad Al-Khalifa ◽

Rowan John Stanley

Keyword(s):

Saudi Arabia ◽

Sequence Stratigraphy ◽

Depositional Environment ◽

Sedimentary Facies ◽

3D Architecture ◽

Clastic Reservoirs

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Characterizing and modeling the Upper Jurassic Arab-D reservoir using outcrop data from Central Saudi Arabia

GeoArabia ◽

10.2113/geoarabia190253 ◽

2014 ◽

Vol 19 (2) ◽

pp. 53-84

Author(s):

Hassan Eltom ◽

Osman Abdullatif ◽

Mohammed Makkawi ◽

Asaad Abdulraziq

Keyword(s):

Saudi Arabia ◽

Gamma Ray ◽

Upper Jurassic ◽

Major And Trace Elements ◽

Carbonate Reservoir ◽

Oil Fields ◽

Small Scale ◽

Well Spacing ◽

Stratigraphic Framework

ABSTRACT Outcrop analogs are used to improve the characterization of reservoir stratigraphy, to understand subsurface facies architecture and heterogeneity, and to overcome the limitations associated with large inter-well spacing within individual oil fields. This study characterized and modeled outcropping strata equivalent to the Upper Jurassic Arab-D carbonate reservoir in Central Saudi Arabia. The study presents qualitative and quantitative sedimentological and petrographic descriptions of lithofacies associations and interprets them within a high-order stratigraphic framework using geostatistical modeling, spectral gamma-ray, geochemistry, petrography and micropaleontology. The sedimentological studies revealed three lithofacies associations, which are interpreted as a gentle slope platform depositional environment comprising nine high-frequency sequences. The biocomponents of the study area show a lower degree of diversity than the subsurface Arab-D reservoir; however, some key biofacies are present and provide indications of the nature of the paleoenvironments. The geochemical results show a strong correlation between the major and trace elements and the reservoir facies, and suggest that the concentrations of elements and their corresponding spectral gamma-ray logs follow the same general upward-shoaling pattern. The 3-D geocellular model captures small-scale reservoir variability, which is reflected in the petrophysical data distribution in the model. This investigation increases the understanding of the stratigraphy of the Arab-D reservoir and provides a general framework for zonation, layering, and lateral stratigraphic correlations.

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A Conversion for Average Grain Size Based on Gamma Ray Well Log: Application in the Second Member of Xujiahe Formation of Anyue Area, Sichuan Basin

Frontiers in Physics ◽

10.3389/fphy.2021.807303 ◽

2021 ◽

Vol 9 ◽

Author(s):

Liang Chen ◽

Hancheng Ji ◽

Nansheng Qiu ◽

Liang Zhang

Keyword(s):

Grain Size ◽

Sichuan Basin ◽

Gamma Ray ◽

Grain Size Analysis ◽

Size Analysis ◽

Sediment Grain Size ◽

Xujiahe Formation ◽

Average Grain Size ◽

Logarithmic Relationship ◽

Clastic Reservoirs

The grain sizes of clastic rock sediments serve as important depositional indicators that are significant in sedimentology and petroleum geology studies. Generally, gamma ray, spontaneous-potential and resistivity well logs are utilized to qualitatively characterize variations in sediment grain size and determine the lithology in clastic reservoirs. However, grain size analysis of modern sedimentary samples collected from active rivers and deltas indicates that the percentage of fine depositional component has a logarithmic relationship with the average grain size in delta and river systems. Using the linear relationship to process the lithology interpretation, siltstones or mudstone is likely to be interpreted as sandstone. Therefore, a logarithmic conversion formula was built up between the gamma ray logs and measured grain size for the second member of the Xujiahe Formation of Anyue Area in the Sichuan Basin. Using the formula, the average grain size and lithology of the exploration wells were determined for the interest intervals. Furthermore, the calculated grain size gives a better understanding of the controlling factors of hydrocarbon-bearing reservoirs in the study area.

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Data Mining Well Logs for Optimum Well Placement

Volume 11: Petroleum Technology ◽

10.1115/omae2020-19025 ◽

2020 ◽

Author(s):

Anuroop Pandey ◽

Mohammed F. Al Dushaishi ◽

Espen Hoel ◽

Svein Hellvik ◽

Runar Nygaard

Keyword(s):

Data Mining ◽

Gamma Ray ◽

Principal Component ◽

Decision Criterion ◽

Classification Model ◽

Well Logs ◽

Well Placement ◽

Reservoir Rocks ◽

Data Mining Approach ◽

Gamma Ray Log

Abstract Well placement with geosteering can get very complex in reservoirs with formation change not simply addressed by changes in the gamma ray log response. This paper uses data mining to characterize complex reservoirs for optimum well placement. The objective of this paper is to develop a data mining process to evaluate non-trivial geologic settings for geosteering reservoir well placement. The well logs’ data was collected from multiple wells in a Norwegian North Sea field, where the reservoir rocks are characterized with high heterogeneities. Principal component analysis was used to recognize data pattern and extract underlying features. The extracted features are then into distinct groups using Hierarchical clustering (HC) analysis. A classification model, that is based on the deviance analysis, was constructed to build a criterion to identify each cluster within a set of well log data. The results show that the data mining approach sufficiently identified highly heterogeneous formations and can be used for geosteering applications. Classification trees defined quantitative decision criterion for the identified clusters. The approach is capable of distinguishing between potential and non-potential steering clusters, as the identified clusters have distinct decision criteria and effectively explain the variations within a section, as verified with the lithology described from core analysis.

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