Stratigraphic Uncertainty Research Articles

Unconventional reservoir characterization using geochemical signatures: Examples from Paleozoic formations, Saudi Arabia

The soaring domestic energy consumption in the Kingdom of Saudi Arabia (KSA) continues to create a demand and supply gap. Paleozoic tight sand and shale reservoirs in KSA are considered potential sources of natural gas that could meet the growing domestic demand. To enhance the exploration and exploitation of these unconventional systems, research focusing on their reservoir quality has tremendously increased in the past few decades. A challenging aspect of these Paleozoic reservoirs is that they have similar lithologies and are poorly constrained biostratigraphically. Therefore, facies analysis, stratigraphic correlation, and geosteering are problematic. This paper describes how chemostratigraphic markers are used to identify and separate individual lithologies. Three hundred and twenty (320) data points were acquired by scanning both end caps of 165 core plug samples from continuously cored sections of three Paleozoic formations. Raw elemental spectral data were acquired using a high-resolution tabletop μXRF system. Multivariate statistical analysis including principal component analysis (PCA), pairwise correlation, and hierarchical clustering of principal components (HCPC) were used to characterize the acquired geochemical values. Eleven (11) chemofacies, within three lithofacies with clearly defined boundaries, were identified. Stratigraphic distribution patterns of the geochemical signatures (e.g., Si, Ca, Mn, Al, K, and Fe), such as sharp truncation at the upper and lower bounds, clearly defined each lithofacies. Thus, key marker elements for each lithofacies and chemozones were identified, even where the lithologies appeared homogeneous. The overall results indicate sediment deposition under varied depositional settings, from fluvial to shallow-marine environments. The results demonstrate that elemental compositional analysis can be used as a discriminating tool for resolving stratigraphic uncertainties. Such data can document subtle variations among samples that appear homogeneous using other techniques.

Data-driven construction of Three-dimensional subsurface geological models from limited Site-specific boreholes and prior geological knowledge for underground digital twin

A digital twin is a digital replica or virtual representations of 3D physical entities in the real world. In practice, it is challenging for 3D modelling of subsurface stratigraphy in an underground digital twin due to insufficient site-specific measurements and a lack of efficient 3D spatial prediction tools. In this study, a data-driven and deep learning method, called IC-XGBoost3D, is proposed to build a 3D geological model from limited site-specific boreholes and 2D training images reflecting prior geological knowledge. Anisotropic stratigraphic relationships are learned from two perpendicular 2D training images, and the extracted stratigraphic statistics serve as the input for pre-training a 2D simulation slice. A sequence of 2D simulation slices is then simulated with constraints by site-specific boreholes and subsequently reassembled into a 3D geological model. Note that the parameters of the deep learning method are calibrated with site-specific data and prior training images before being applied to develop the geological model. The model performance is demonstrated and validated using an illustrative example. The proposed method can efficiently generate an anisotropic 3D geological model as a point cloud from two perpendicular training images and sparse boreholes with a high prediction accuracy. More importantly, the proposed method not only infers the most probable 3D geological domain, but also provides a quantitative evaluation of associated 3D stratigraphic uncertainty. Effects of irregular borehole spacing and single training image on the simulation performance are also investigated.

Full probability design of soil slopes considering both stratigraphic uncertainty and spatial variability of soil properties

Full probability design of soil slopes considering both stratigraphic uncertainty and spatial variability of soil properties

Influence of geological uncertainty on the design of OWTF monopiles

This paper presents a methodology to assess the influence of geological uncertainty (stratigraphic uncertainty) on designing an offshore wind turbine foundation (OWTF). To consider the stratigraphic uncertainty, we create a synthetic stratigraphic model (SSM) and then sample multiple sets of boreholes to develop a series of stratigraphic models, each with a different degree of uncertainty (entropy). Using Markov random field (MRF) theory, these stratigraphic models were simulated, and their entropies were evaluated. The results indicate the entropies of the stratigraphic models decrease as the number of boreholes increases. The OWTF monopile is then designed based on these stratigraphic models with different entropy levels. Next, Monte Carlo simulation (MCS) is used to evaluate the failure probability of the design, considering uncertainties of the stratigraphic model and soil properties. Then, two monopile designs simulating piles located at different stratigraphic configurations are analyzed to assess the effects of stratigraphic uncertainty and strength parameter variability on their failure probabilities. Finally, insights gained regarding the effect of stratigraphic uncertainty on the OWTF monopile design are discussed.

Assessment of reclamation-induced consolidation settlement considering stratigraphic uncertainty and spatial variability of soil properties

Consolidation analysis is a key task for reclamation design. Although consolidation is a long-term process, acceleration of consolidation is often preferred for speeding up the reclamations. Before proposing measures to accelerate the consolidation and reclamation process, it is imperative to have an accurate prediction of consolidation settlement for fine-grained materials, which is greatly affected by spatial distribution of subsurface zones with different soil types (i.e., stratigraphic heterogeneities and uncertainty) and spatial variability of soil properties. In current practice, calculation of consolidation settlement often uses simplified stratigraphic boundaries and deterministic consolidation parameters without considering stratigraphic uncertainty or soil property spatial variability. The oversimplified practice might result in unconservative estimations of consolidation settlement and pose threats to safety and serviceability of constructed facilities on reclaimed lands. In this study, a stochastic framework is proposed for consolidation settlement assessment with explicit modeling of stratigraphic uncertainty and spatial variability of soil properties by machine learning and random field simulation from limited site investigation data. Performance of the proposed framework is demonstrated using an illustrative example. Results indicate that the proposed method effectively generates multiple realizations of geological cross section and random field samples of geotechnical properties from limited measurements and offers valuable insights into spatial distribution of the estimated total primary consolidation settlement curves and angular distortion.

Coupled characterization of stratigraphic and geo-properties uncertainties – A conditional random field approach

Site characterization, which aims to characterize the subsurface stratigraphic configuration and the associated geo-properties, has long been a significant challenge in geological and geotechnical practice. Due to the complexity and inherent spatial variability of the geological bodies and the limited availability of borehole data, uncertainty is unavoidable in the characterized subsurface stratigraphic configuration and the associated geo-properties. In previous studies, the stratigraphic uncertainty and the geo-properties uncertainty were characterized separately. This paper proposes a conditional random field approach for a coupled characterization of stratigraphic and geo-properties uncertainties. The spatial correlation of the stratum existence between different subsurface elements and the spatial correlation of geo-properties are characterized by two autocorrelation functions, determined with the maximum likelihood principle. With the knowledge of the spatial correlation of the stratum existence, the stratigraphic configuration can be sampled using a modified random field approach. Then, the spatial correlation of the geo-properties is updated based on the sampled stratigraphic configuration. With the updated spatial correlation of the geo-properties, the spatial distribution of the geo-properties can readily be simulated with the conditional random field theory. The effectiveness of the proposed approach is demonstrated through a case study of probabilistic site characterization of an offshore wind farm site in Taiwan. To extend the applicability of the proposed approach, a probabilistic evaluation of liquefaction potential at this site under a given seismic shaking level is performed.

Prehistoric earthquakes on the Banning strand of the San Andreas fault, North Palm Springs, California

AbstractWe studied a paleoseismic trench excavated in 2017 across the Banning strand of the San Andreas fault and herein provide the first detailed record of ground-breaking earthquakes on this important fault in Southern California. The trench exposed an ~40-m-wide fault zone cutting through alluvial sand, gravel, silt, and clay deposits. We evaluated the paleoseismic record using a new metric that combines event indicator quality and stratigraphic uncertainty. The most recent paleoearthquake occurred between 950 and 730 calibrated years B.P. (cal yr B.P.), potentially contemporaneous with the last rupture of the San Gorgonio Pass fault zone. We interpret five surface-rupturing earthquakes since 3.3–2.5 ka and eight earthquakes since 7.1–5.7 ka. It is possible that additional events have occurred but were not recognized, especially in the deeper (older) section of the stratigraphy, which was not fully exposed across the fault zone. We calculated an average recurrence interval of 380–640 yr based on four complete earthquake cycles between earthquakes 1 and 5. The average recurrence interval is thus slightly less than the elapsed time since the most recent event on the Banning strand. The average recurrence interval on the Banning strand is thus intermediate between longer intervals published for the San Gorgonio Pass fault zone (~1600 yr) and shorter intervals on both the Mission Creek strand of the San Andreas fault (~215 yr) and the Coachella section (~125 yr) of the San Andreas fault.

Probabilistic characterization of subsurface stratigraphic configuration with modified random field approach

Accurate and precise characterization of the subsurface stratigraphic configuration (geological model) at a given site is crucial to geotechnical engineering work. The uncertainty in the derived stratigraphic configuration can be significant, due to the strata's complexity and inherent spatial variability coupled with the limited availability of borehole data. The characterization and reduction of this uncertainty should be part of any site characterization project. This paper presents a method for characterization of the subsurface stratigraphic configuration with limited borehole data. Within the framework of the proposed method, the spatial correlation between the existence of a stratum in one subsurface zone and that in the other subsurface zone (or the spatial correlation of the existence of the stratum) is captured by an autocorrelation function determined with the maximum likelihood principle. The initial stratigraphic configurations are first sampled with the conditional random field theory. Next, the maximum-a-posteriori (MAP) estimates of the initial stratigraphic configurations are derived using Markov Chain Monte Carlo (MCMC) and taken as the final stratigraphic realizations. The effectiveness of the proposed method and its advantages over the existing stratigraphic characterization methods are demonstrated through a series of comparative analyses. The versatility of the new approach in modeling the 3-D stratigraphic configuration is further revealed through a case study of a site in Western Australia. This paper adds to the literature on stratigraphic uncertainty characterization and provides a basis for a risk-based geotechnical assessment that considers geological and geotechnical uncertainties.

Quantificando a incerteza estratigráfica na modelagem de águas subterrâneas para projeto de infraestrutura

A methodology to quantify the stratigraphic uncertainty of the aquifer bottom is used in assessing the impact of sheet piles on the water table in the vicinity of a motorway. The method includes uncertainties on model parameters and depth of sheet piles. While parameter uncertainty dominates when simulating the existing groundwater conditions, the stratigraphic uncertainty dominates when predicting the impacts of the motorway sheet piles. The uncertainty of groundwater head predictions is a key element in risk assessments for infrastructure projects, where groundwater affects construction costs. While geological structural uncertainty often is a dominating source of uncertainty in large-scale water-resource studies, stratigraphic uncertainty (defined as the uncertainty of the location of geological boundaries between units/facies) becomes more important for small-scale infrastructure projects. The methodologies used so far for handling stratigraphic uncertainty typically use a somewhat simplistic approach basing the uncertainties of the geological surfaces on the kriging variance. The proposed methodology has two novel elements. Firstly, the uncertainties in the geological interpretation of the borehole data are explicitly included. Secondly, conditional sequential Gaussian simulation (sGs) is used to quantify the uncertainties. The advantage of sGs over standard kriging-based approaches is that sGs allows descriptions of small-scale variations that are crucial in some contexts. The methodology was tested on a case site in Denmark where a new motorway has been constructed below the water table and with sheet-pile walls designed to penetrate the aquifer down to 1 m above the aquifer bottom.

Smart determination of borehole number and locations for stability analysis of multi-layered slopes using multiple point statistics and information entropy

Subsurface stratigraphy of multi-layered slopes is essential and crucial for slope stability analysis. It is usual practice for engineers to interpret stratigraphic boundaries separating different soil layers using both site investigation data and prior knowledge of local geology, but such practice might encounter significant challenge when the site data are very limited. In addition, uncertainty in stratigraphic boundaries has not been explicitly or quantitatively considered in planning of site investigation (e.g., determination of borehole number and locations). There lacks a quantitative and objective tool to determine the optimal locations and number of boreholes for slope stability analysis while accounting for stratigraphic uncertainty. In this study, a smart sampling strategy based on multiple point statistics and information entropy is proposed for delineation of slope subsurface stratigraphy and planning of geotechnical boreholes. It is a data-driven approach that enables an ensemble of prior knowledge within a training image using multiple point statistics. The proposed method not only provides evolution of the most probable interpolation from sparse measurements and the associated interpolation uncertainties, but also adaptively determines the optimal locations of boreholes. Effectiveness of the proposed method is illustrated and validated through both a simulation example and a real case. It is found that the data-driven framework can automatically identify locations of largest interpolation uncertainty within a multi-layered slope conditional on its outcrops, and that the associated stratigraphic uncertainty gradually reduces as borehole number increases. More importantly, the optimal number and locations of boreholes required for slope stability analysis are adaptively determined by the proposed method.

Slope stability analysis using deterministic and probabilistic approaches for poorly defined stratigraphies

The stability of slopes directly affects human lives, the environment, and the economy. Inaccurate geological profiles within numerical slope stability models can lead to potentially catastrophic consequences when model conditions do not appropriately reflect real-life stratigraphy. In cases where localised deposits are prevalent, probabilistic methods are often necessary to accommodate for unknown or poorly defined stratigraphies. Currently, there are no commercial geotechnical software packages that simulate probabilistic constitutive behaviour of materials within finite element methods for large-scale stratigraphic analysis. Instead, commercially available probabilistic methods such as the random limit equilibrium method are incapable of incorporating non-linear constitutive soil behaviour. For this reason, advanced constitutive models are seldom coupled with probabilistically varying soil layers or spatially variable soil parameters. The objective of this research is the implementation of a simplified method for probabilistic stratigraphic analysis within a commercially available FE environment, providing a technique to assess the effects of stratigraphic uncertainty on slope stability. The proposed method is presented, highlighting the impact of localised thin layers of soft material as well as their frequency and location on the slope of an operational open-pit mine. The significance of these stratigraphic effects is presented through a case study of Australia’s second-largest open-pit mine, at which the stability of a collapsed coal slope is analysed. To improve the reliability of the finite element method for slope stability assessment, the Monte Carlo approach has been incorporated to consider varying shear strength distributions for models incorporating advanced constitutive behaviour. Thicker probabilistically generated deposits of silty material resulted in increased slope Factors of Safety. Similarly, greater proportions of silty deposits within a predominantly clayey interseam produced larger safety factors than slopes without localised thin silty layers. Stratigraphic analysis indicated that the Factor of Safety was most sensitive to localised silt layers at depths greater than 83 m below ground level.

Re-assessing the Upper Permian Stratigraphic Succession of the Northern Sydney Basin, Australia, by CA-IDTIMS

High precision Chemical abrasion-isotope dilution thermal ionisation mass spectrometry (CA-IDTIMS) U-Pb zircon results from tuff marker beds that are interstratified within the Upper Permian deposits of the northern Sydney Basin add constraints on the timing of sediment deposition, and afford a better understanding of the regional stratigraphy. The results indicate a magmatic influence during the deposition of the sediments, with episodic events spanning at least from 255.65 ± 0.08 to 255.08 ± 0.09 Ma. The zircon data suggest that the studied sedimentary rocks and tuffs have accumulated simultaneously over a short time interval, which contrasts with current stratigraphic models that suggest a much greater period of deposition and stratigraphic thickness. Therefore, an updated stratigraphic correlation of the basin is suggested, which combines the presently defined Lambton, Adamstown, and Boolaroo sub-groups into a single Lambton sub-group. This updated correlation framework is stratigraphically and geochronologically constrained and provides a more precise exploration model for the northern Sydney Basin. This case study highlights the valuable contribution of the CA-IDTIMS method in intrabasinal correlations of sedimentary successions, when integrated with a robust sedimentological framework, to minimize the stratigraphic uncertainties.

Aridity synthesis for eight selected key regions of the global climate system during the last 60 000 years

Abstract. A compilation of the published literature on dust content in terrestrial and marine sediment cores was synchronized with pollen data and speleothem growth phases on the Greenland Ice Core Chronology 2005 (GICC05) time axis. Aridity patterns for eight key areas of the global climate system have been reconstructed for the last 60 000 years. These records have different time resolutions and different dating methods, i.e. different types of stratigraphy. Nevertheless, all regions analysed in this study show humid conditions during early Marine Isotope Stage 3 (MIS3) and the early Holocene or deglaciation, but not always at the same time. Such discrepancies have been interpreted as regional effects, although stratigraphic uncertainties may affect some of the proposed interpretations. In comparison, most of the MIS2 interval becomes arid in all of the Northern Hemisphere records, but the peak arid conditions of the Last Glacial Maximum (LGM) and Heinrich event 1 differ in duration and intensity among regions. In addition, we also compare the aridity synthesis with modelling results using a global climate model (GCM). Indeed, geological archives and GCMs show agreement on the aridity pattern for the Holocene or deglaciation, for the LGM and for late MIS3.

A full sequence of the Matuyama\u2013Brunhes geomagnetic reversal in the Chiba composite section, Central Japan

Geological records of the Matuyama–Brunhes (M–B) geomagnetic reversal facilitate the development of an age model for sedimentary and volcanic sequences and help decipher the dynamics of the Earth’s magnetic field. However, the structure of the geomagnetic field during the M–B geomagnetic reversal remains controversial due to its complex field behavior. In this study, we conducted paleo- and rock-magnetic analyses of samples from the Chiba composite section (CbCS), a continuous and expanded marine succession in Central Japan, to reconstruct the full sequence of the M–B geomagnetic reversal. We define an average stratigraphic position of the M–B boundary and estimate its age based on three sections in the CbCS and a neighboring drill core, TB-2. The average stratigraphic position of the M–B boundary in the CbCS is established at 1.1 ± 0.3 m above a widespread volcanic ash bed (the Byk-E tephra). Assuming a chronological error associated with orbital tuning of 5 kyr and stratigraphic uncertainty of 0.4 kyr, the M–B boundary in CbCS is at 772.9 ± 5.4 ka (1σ). The virtual geomagnetic pole, which is calculated from the paleomagnetic directions, shows several short fluctuations between 783 and 763 ka, with concomitant decreases in geomagnetic field intensity index. After termination of the field instabilities, the field intensity recovered and became higher than before the M–B boundary, with a stable normal polarity direction. The paleomagnetic records in the CbCS exhibit a field asymmetry between the axial dipole decay and field recovery, providing a full sequence of the M–B reversal, suggesting that the non-axial dipole field dominated several times during periods ca. 20 kyr long across the M–B boundary, due to depletion in the main axial dipole component. Our results provide probably the most detailed sedimentary record of the M–B geomagnetic reversal and offer valuable information to further understand the mechanism and dynamics of geomagnetic reversals.Graphical abstract

Geology of Bajos de Totuma Hidropower Project (5 MW), Chiriqui, Panama

Bajos de Totuma Hydropower Project study area is located in west Panama, near to Costa Rica-Panama border line. The hydraulic scheme of the project includes a small intake in the Colorado River, an initial conduction, a superficial pipeline, pressure tank, penstock, a powerhouse and generates 5 MW of power. Subduction dynamics process south of the study area is complex, standing out structures such as Panama Fracture Zone, Cocos Ridge, Tisingal and Tisingal volcanos. The study area is composed mostly by Paleogene-Neogene bedrock and Quaternary age volcanic rocks and materials (pyroclastic-epiclastic, PE) originated in West Panama volcanic range (Tisingal and Tisingal volcanos, which are among the highest mountains in Panama). BTHPP is located in a complex volcanic geological setting. Many different types of volcanic rocks and related materials are present along project scheme. It is highly probable that most of those materials were originated during Tisingal volcano major explosive activity some 1.6 million years ago, so probably most of the rocks in the area are allochthonous and/or related to major Tisingal lateral explosion and resulting pyroclastic flow some 1.6 million years ago. Despite major stratigraphic uncertainties, this investigation contributes to a relative fair understanding of the geotechnical conditions and parameters present in every project proposed work, this is, intake, tunnels, conducting pipelines, surge tank, penstock, and power house.

Stratigraphic uncertainty characterization using generalized coupled Markov chain

Stratigraphic uncertainty widely exists in geotechnical structures. An efficient generalized coupled Markov chain (GCMC) model was proposed to simulate the stratigraphic uncertainty in the past. This model, however, cannot be directly applied to geotechnical problems because of the difficulty in directly estimating the horizontal transition probability matrices (HTPMs) of the GCMC from boreholes with large hole-to-hole distance. This paper, therefore, aims at addressing the above problem by using a maximum likelihood estimation (MLE) method and utilizing the MLE modified GCMC model to characterize stratigraphic uncertainty. In the framework of the GCMC, the validity of the proposed method is verified, and information entropy method is adopted to quantify the stratigraphic uncertainty. As an illustration, the proposed model is applied to a construction site in Hong Kong to characterize the stratigraphic uncertainty. A systematic comparison of coupled Markov chain (CMC) and GCMC model for stratigraphic uncertainty simulation was conducted. The influences of borehole layout scheme on transition probability matrices (TPMs) estimation and stratigraphic uncertainty simulation are explored. Results showed that the result of stratigraphic uncertainty simulation of the GCMC model is more reasonable than that of the CMC model. The borehole layout scheme is very important for estimating TPMs and significantly influences the stratigraphic uncertainty simulation. The information entropy map has the potential to become a useful guideline for the design of the borehole layout scheme in geotechnical engineering practice.

Stratigraphic uncertainty modelling with random field approach

Due to the complexity and inherent spatial variability of the strata and the limited availability of borehole information, the subsurface stratigraphic configuration at a site is hard to characterize accurately, which gives rise to stratigraphic uncertainty. This paper presents a random field-based approach for modelling the stratigraphic uncertainty, in which, the spatial correlation of the stratum existence between different subsurface elements is characterized by an autocorrelation function, and the probability of the existence of a particular stratum in a given non-borehole element is determined according to the derived spatial correlations. With the existence probabilities calculated, Monte Carlo simulation (MCS) is used for sampling the possible realizations of the stratigraphic configuration. The number of the MCS samples is determined based upon an information entropy analysis. To illustrate the effectiveness of this new approach, a set of hypothetical examples (with different stratigraphic settings) are studied; and, the advantages of this new approach over the existing stratigraphic uncertainty modelling approaches are depicted through a comparative analysis. Finally, this new approach is applied to Majiagou Landslide for a probabilistic stability analysis. The influences of the stratigraphic uncertainty on the stability of this landslide and the location of the slip surface are revealed.

Olson's Gap or Olson's Extinction? A Bayesian tip-dating approach to resolving stratigraphic uncertainty.

Adaptive radiations and mass extinctions are of critical importance in structuring terrestrial ecosystems. However, the causes and progress of these transitions often remain controversial, in part because of debates surrounding the completeness of the fossil record and biostratigraphy of the relevant fossil-bearing formations. The early-middle Permian, when a substantial faunal turnover in tetrapods coincided with a restructuring of the trophic structure of ecosystems, is such a time. Some have suggested the transition is obscured by a gap in the tetrapod fossil record (Olson's Gap), while others suggest a correlation between North American and Russian tetrapod-bearing formations allows the interval to be documented in detail. The latter biostratigraphic scheme has been used to support a mass extinction at this time (Olson's Extinction). Bayesian tip-dating methods used frequently in phylogenetics are employed to resolve this debate. Bayes factors are used to compare the results of analyses incorporating tip age priors based on different stratigraphic hypotheses, to show which stratigraphic scheme best fits the morphological data and phylogeny. Olson's Gap is rejected, and the veracity of Olson's Extinction is given further support. Tip-dating approaches have great potential to resolve debates surrounding the stratigraphic ages of critical formations where appropriate morphological data is available.

On Quantifying Stratigraphic, Chronologic, and Paleo Flux Uncertainties in Paleoceanography

On Quantifying Stratigraphic, Chronologic, and Paleo Flux Uncertainties in Paleoceanography

A new crocodylomorph tooth assemblage from the Tataouine Basin and comments on the stratigraphic context of the Douiret Formation

A new crocodylomorph tooth assemblage from the Lower Member of the Douiret Formation (uppermost Jurassic–lowermost Cretaceous) in southeastern Tunisia is described. These teeth have been grouped into five morphotypes based on their diagnostic morphological features. The sample includes teeth, which have not been reported until now, such as non-Machimosaurini teleosauroid teeth, and labiolingually compressed tooth crowns with cutting edges devoid of serrations. Certain minor morphometric differences have been interpreted as ontogenetic or being possibly related to the position of the teeth in the jaws. Three trophic entities have subsequently been defined on the basis of the morphological characteristics of the teeth, and a possible niche partitioning between at least three crocodylomorph taxa is highlighted for the first time in the Tataouine Basin. On the other hand, the stratigraphic context of the Douiret Formation is thoroughly discussed in order to show how stratigraphic uncertainties could significantly impact previous attempts at reconstructing the macroevolutionary history of Crocodylomorpha. The latter should be treated with caution when the stratigraphic context of the fossil bearing formation remains a subject of debate.