Application of Lithofacies Modelling in Enhancing the Well Productivity; An Example from Eagle Ford Shale

Sahoo, Ajit Kumar; Mukherjee, R.M.; Mukherjee, Angshuman; Mukherjee, Diya; Srivastava, Mukul

doi:10.15530/urtec-2014-1921815

Cited by 5 publications

(1 citation statement)

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“…The exploration practice shows that the reservoir characteristics are important for shale gas accumulation. However, the key to the study of reservoir characteristics is to identify favorable lithofacies for commercial development (Jacobi et al, 2008;Sahoo et al, 2014). Due to the strong heterogeneity of shale reservoirs from the macro-scale to micro-scale, it is difficult to predict effective shale gas reservoirs (Chen et al, 2015;Jiang et al, 2015).…”

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confidence: 99%

Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi marine shale in the southeast Sichuan Basin, China

Tang

Jiang

Huang

et al. 2016

Journal of Natural Gas Science and Engineering

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Based on a detailed description and analysis of outcrops and drilling cores, onsite gas desorption, and laboratory testing data, shale lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi Formation marine shale in the southeast Sichuan Basin have been studied. Twelve types of shale lithofacies are classified based on the organic matter content and mineral composition, of which 9 types were identified in the study area based on their dramatically differences in color, grain size, lamination, organic matter content, mineralogy, density, and other physical properties. The bottom of the Longmaxi shale Formation is primarily organic-rich siliceous shale with stable distribution of thickness and good continuity. The upper section has characteristics of rapid vertical and lateral change in lithofacies, exhibiting a strong spatial heterogeneity. Organic-rich siliceous shale in the lower section, showing the highest content of gas desorption in situ, has a high content of organic matter, a high brittleness index and good permeability, which is conducive to shale gas storage, hydraulic fracturing, and exploitation. Organic-rich argillaceous shale was also observed to have the highest methane adsorption capacity. The interval with lithofacies association of organic-rich siliceous shale with organic-rich argillaceous shale interlayer is the pay zone for shale gas generation and accumulation.

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Section: Introductionmentioning

confidence: 99%

Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi marine shale in the southeast Sichuan Basin, China

Tang

Jiang

Huang

et al. 2016

Journal of Natural Gas Science and Engineering

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Lithofacies classification in the Marcellus Shale by applying a statistical clustering algorithm to petrophysical and elastic well logs

2016

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Interpreting shale lithofacies is an important step in identifying productive zones in the Marcellus Shale gas play; the target reservoir can be less than 3 m (10 ft) thick with overlying shales that appear similar on certain petrophysical well logs and in the core. However, these nonreservoir-quality shales contain widely varying organic and mechanical properties. To distinguish between reservoir- and nonreservoir-quality shale facies, this classification method applies a pattern-recognition algorithm, expectation maximization, to a set of commonly available petrophysical and elastic well logs to create 1D shale facies models along the wellbore. The statistical algorithm classifies the petrophysical and elastic well-log data into defined facies using the theory that each well log contains a distribution of Gaussian curves for each facies. The method is applied to 12 wells across Pennsylvania and northern West Virginia, and it is able to discriminate between shale facies based on organic content and brittleness, characteristics which are not always evident in core. To verify the geologic accuracy of the facies models, the results are compared with the core data, well logs, mudlogs, and regional stratigraphic studies when available. In addition, we were able to designate a lithofacies-defined top to the Marcellus Formation in parts of the Appalachian Basin where the gradational contact with the overlying Mahantango Formation is poorly defined on petrophysical logs.

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Stratigraphic characterization of the Eagle Ford shale to identify the best landing zone: A semianalytical workflow

2022

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Placement of the horizontal well within the best landing zone is critical to maximize well productivity, thus identification of the best landing zone is important. This paper illustrates an integrated semi-analytical workflow to carry out the stratigraphic characterization of the Eagle Ford shale to identify the best landing zone. The objective of this work is twofold: 1) to establish a workflow for stratigraphic characterization and 2) to understand the local level variability in the well performance.To establish the workflow, we have used the production data, petrophysical information and regional reservoir property maps. As a first step of the workflow, we subdivided the Eagle Ford shale into nine smaller stratigraphic units using the wireline signatures and outcrop study. In the second step, we have used statistical methods such as linear regression, fuzzy groups and theory of granularity to capture the relationship between the geological parameters and the well performances. In this step, we identified volume of clay (Vclay), hydrocarbon filled porosity (HCFP) and total organic carbon (TOC) as key drivers of the well performance. In the third step, we characterized the nine smaller units and identified four stratigraphic units as good reservoirs with two being the best due to their low Vclay, high HCFP and high TOC content.Finally, we reviewed the well paths of four horizontal wells with respect to the best stratigraphic units. We observed that production behavior of these wells is possibly driven by their lateral placement. The better producing wells are placed within the middle of the best stratigraphic units whereas the poor wells are going out the best stratigraphic units. This investigation provides a case study that demonstrates the importance of integrating datasets to identify best landing zones and the suggested workflow can be applied to other areas and reservoirs to better identify targetable zones.

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Application of Lithofacies Modelling in Enhancing the Well Productivity; An Example from Eagle Ford Shale

Cited by 5 publications

References 0 publications

Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi marine shale in the southeast Sichuan Basin, China

Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi marine shale in the southeast Sichuan Basin, China

Lithofacies classification in the Marcellus Shale by applying a statistical clustering algorithm to petrophysical and elastic well logs

Stratigraphic characterization of the Eagle Ford shale to identify the best landing zone: A semianalytical workflow

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