Workflow for improvement of 3D anisotropic CSEM resistivity inversion and integration with seismic using cross-gradient constraint to reduce exploration risk in a complex fold-thrust belt in offshore northwest Borneo

2018 ◽  
Vol 6 (3) ◽  
pp. SG49-SG57 ◽  
Author(s):  
Max A. Meju ◽  
Ahmad Shahir Saleh ◽  
Randall L. Mackie ◽  
Federico Miorelli ◽  
Roger V. Miller ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Three Dimensional ◽  
Structural Complexity ◽  
Hydrocarbon Exploration ◽  
Parameter Estimates ◽  
Thrust Belt ◽  
Exploration Risk ◽  
Resistivity Logs ◽  
Geologic Interpretation ◽  
Reservoir Parameter

The focus of hydrocarbon exploration has now moved into frontier regions where structural complexity, heterogeneous overburden, and hydrocarbon system fundamentals are significant challenges requiring an integrated exploration approach. Three-dimensional controlled-source electromagnetic (CSEM) anisotropic resistivity imaging is emerging as a technique to combine with seismic imaging in such regions. However, the typically reconstructed horizontal resistivity [Formula: see text] and vertical resistivity [Formula: see text] models often have conflicting depth structures that are difficult to explain in terms of subsurface geology. It is highly desirable to reduce ambiguity or subjectivity in depth interpretation of [Formula: see text] and [Formula: see text] models and also achieve comparability with other coincidentally located subsurface models. We have developed a workflow for integrating information from seismic well-based inversion, interpreted seismic horizons, and resistivity well logs in a cross-gradient-guided simultaneous 3D CSEM inversion for geologically realistic [Formula: see text] and [Formula: see text] models whose parameter estimates for a selected reservoir interval can then be better optimized to aid reservoir characterization. We developed our workflow using exploration data from a complex fold-thrust belt. We found that the integrated cross-gradient approach led to [Formula: see text] and [Formula: see text] models that have a common depth structure, are consistent with seismic and resistivity logs, and are hence less ambiguous for geologic interpretation and reservoir parameter estimation.

Seismic image-guided 3D inversion of marine controlled-source electromagnetic and magnetotelluric data

2020 ◽  
Vol 8 (4) ◽  
pp. SS1-SS13 ◽  
Author(s):  
Randall L. Mackie ◽  
Max A. Meju ◽  
Federico Miorelli ◽  
Roger V. Miller ◽  
Carsten Scholl ◽  
...  
Keyword(s):  
Structural Complexity ◽  
Structural Similarity ◽  
Hydrocarbon Exploration ◽  
Magnetotelluric Data ◽  
Controlled Source ◽  
Seismic Image ◽  
New Frontier ◽  
Gradient Fields ◽  
Resistivity Model ◽  
Geologic Interpretation

Geologic interpretation of resistivity models from marine controlled-source electromagnetic (CSEM) and magnetotelluric (MT) data for hydrocarbon exploration and reservoir monitoring can be problematic due to structural complexity and low-resistivity contrasts in sedimentary units typically found in new frontier areas. It is desirable to reconstruct 3D resistivity structures that are consistent with seismic images and geologic expectations of the subsurface to reduce uncertainty in the evaluation of petroleum ventures. Structural similarity is achieved by promoting a cross-gradient constraint between external seismically derived gradient fields and the inversion resistivity model. The gradient fields come from coherency weighted structure tensors computed directly from the seismic volume. Consequently, structural similarity is obtained without the requirement for any horizon interpretation or picking, thus significantly reducing the complexity and effort. We have determined the effectiveness of this approach using CSEM, MT, and seismic data from a structurally complex fold-thrust belt in offshore northwest Borneo.

Ray-based stochastic inversion of prestack seismic data for improved reservoir characterization

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. R85-R97 ◽  
Author(s):  
Dennis van der Burg ◽  
Arie Verdel ◽  
Kees Wapenaar
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Normal Incidence ◽  
New Method ◽  
Parameter Estimates ◽  
Lateral Velocity ◽  
Stochastic Inversion ◽  
Reservoir Parameter ◽  
Inversion Techniques ◽  
Amplitude Versus

Trace inversion for reservoir parameters is affected by angle averaging of seismic data and wavelet distortion on the migration image. In an alternative approach to stochastic trace inversion, the data are inverted prestack before migration using 3D dynamic ray tracing. This choice makes it possible to interweave trace inversion with Kirchhoff migration. The new method, called ray-based stochastic inversion, is a generalization of current amplitude versus offset/amplitude versus angle (AVO/AVA) inversion techniques. The new method outperforms standard stochastic inversion techniques in cases of reservoir parameter estimation in a structurally complex subsurface with substantial lateral velocity variations and significant reflector dips. A simplification of the method inverts the normal-incidence response from reservoirs with approximately planar layering at the subsurface target locations selected for inversion. It operates along raypaths perpendicular to the reflectors, the direction that offers optimal resolution to discern layering in a reservoir. In a test on field data from the Gulf of Mexico, reservoir parameter estimates obtained with the simplified method, the estimates found by conventional stochastic inversion, and the actual values at a well drilled after the inversion are compared. Although the new method uses only 2% of the prestack data, the result indicates it improves accuracy on the dipping part of the reservoir, where conventional stochastic inversion suffers from wavelet stretch caused by migration.

Direct reservoir parameter estimation using joint inversion of marine seismic AVA and CSEM data

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. C1-C13 ◽  
Author(s):  
G. Michael Hoversten ◽  
Florence Cassassuce ◽  
Erika Gasperikova ◽  
Gregory A. Newman ◽  
Jinsong Chen ◽  
...  
Keyword(s):  
Water Saturation ◽  
Joint Inversion ◽  
Hydrocarbon Exploration ◽  
Rock Properties ◽  
Parameter Estimates ◽  
Angle Of Incidence ◽  
Model Errors ◽  
Inversion Algorithm ◽  
Fluid Saturation ◽  
Reservoir Parameter

Accurately estimating reservoir parameters from geophysical data is vitally important in hydrocarbon exploration and production. We have developed a new joint-inversion algorithm to estimate reservoir parameters directly, using both seismic amplitude variation with angle of incidence (AVA) data and marine controlled-source electromagnetic (CSEM) data. Reservoir parameters are linked to geophysical parameters through a rock-properties model. Errors in the parameters of the rock-properties model introduce errors of comparable size in the reservoir-parameter estimates produced by joint inversion. Tests of joint inversion on synthetic 1D models demonstrate improved fluid saturation and porosity estimates for joint AVA-CSEM data inversion (compared with estimates from AVA or CSEM inversion alone). A comparison of inversions of AVA data, CSEM data, and joint AVA-CSEM data over the North Sea Troll field, at a location for which we have well control, shows that the joint inversion produces estimates of gas saturation, oil saturation, and porosity that are closest (as measured by the rms difference, the [Formula: see text] norm of the difference, and net values over the interval) to the logged values. However, CSEM-only inversion provides the closest estimates of water saturation.

scholarly journals Human iPSC-Based Modeling of Central Nerve System Disorders for Drug Discovery

2021 ◽  
Vol 22 (3) ◽  
pp. 1203
Author(s):  
Lu Qian ◽  
Julia TCW
Keyword(s):  
Drug Discovery ◽  
Disease Modeling ◽  
Three Dimensional ◽  
Structural Complexity ◽  
Induced Pluripotent Stem Cell ◽  
Cell Types ◽  
Central Nerve System ◽  
Human Ipscs ◽  
Nerve System

A high-throughput drug screen identifies potentially promising therapeutics for clinical trials. However, limitations that persist in current disease modeling with limited physiological relevancy of human patients skew drug responses, hamper translation of clinical efficacy, and contribute to high clinical attritions. The emergence of induced pluripotent stem cell (iPSC) technology revolutionizes the paradigm of drug discovery. In particular, iPSC-based three-dimensional (3D) tissue engineering that appears as a promising vehicle of in vitro disease modeling provides more sophisticated tissue architectures and micro-environmental cues than a traditional two-dimensional (2D) culture. Here we discuss 3D based organoids/spheroids that construct the advanced modeling with evolved structural complexity, which propels drug discovery by exhibiting more human specific and diverse pathologies that are not perceived in 2D or animal models. We will then focus on various central nerve system (CNS) disease modeling using human iPSCs, leading to uncovering disease pathogenesis that guides the development of therapeutic strategies. Finally, we will address new opportunities of iPSC-assisted drug discovery with multi-disciplinary approaches from bioengineering to Omics technology. Despite technological challenges, iPSC-derived cytoarchitectures through interactions of diverse cell types mimic patients’ CNS and serve as a platform for therapeutic development and personalized precision medicine.

scholarly journals The role of hydrological transience in peatland pattern formation

2013 ◽  
Vol 1 (1) ◽  
pp. 29-43 ◽  
Author(s):  
P. J. Morris ◽  
A. J. Baird ◽  
L. R. Belyea
Keyword(s):  
Steady State ◽  
Hydraulic Properties ◽  
Three Dimensional ◽  
Structural Complexity ◽  
Plant Litter ◽  
Future Climate Change ◽  
Litter Production ◽  
Landscape Models ◽  
Water Tables

Abstract. The sloping flanks of peatlands are commonly patterned with non-random, contour-parallel stripes of distinct micro-habitats such as hummocks, lawns and hollows. Patterning seems to be governed by feedbacks among peatland hydrological processes, plant micro-succession, plant litter production and peat decomposition. An improved understanding of peatland patterning may provide important insights into broader aspects of the long-term development of peatlands and their likely response to future climate change. We recreated a cellular simulation model from the literature, as well as three subtle variants of the model, to explore the controls on peatland patterning. Our models each consist of three submodels, which simulate: peatland water tables in a gridded landscape, micro-habitat dynamics in response to water-table depths, and changes in peat hydraulic properties. We found that the strength and nature of simulated patterning was highly dependent on the degree to which water tables had reached a steady state in response to hydrological inputs. Contrary to previous studies, we found that under a true steady state the models predict largely unpatterned landscapes that cycle rapidly between contrasting dry and wet states, dominated by hummocks and hollows, respectively. Realistic patterning only developed when simulated water tables were still transient. Literal interpretation of the degree of hydrological transience required for patterning suggests that the model should be discarded; however, the transient water tables appear to have inadvertently replicated an ecological memory effect that may be important to peatland patterning. Recently buried peat layers may remain hydrologically active despite no longer reflecting current vegetation patterns, thereby highlighting the potential importance of three-dimensional structural complexity in peatlands to understanding the two-dimensional surface-patterning phenomenon. The models were highly sensitive to the assumed values of peat hydraulic properties, which we take to indicate that the models are missing an important negative feedback between peat decomposition and changes in peat hydraulic properties. Understanding peatland patterning likely requires the unification of cellular landscape models such as ours with cohort-based models of long-term peatland development.

Lithostratigraphic and tectonic framework of Jurassic and Cretaceous Intermontane sedimentary basins of south-central British Columbia1This article is one of a series of papers published in this Special Issue on the theme of New insights in Cordilleran Intermontane geoscience: reducing exploration risk in the mountain pine beetle-affected area, British Columbia.

2011 ◽  
Vol 48 (6) ◽  
pp. 870-896 ◽  
Author(s):  
Janet Riddell
Keyword(s):  
British Columbia ◽  
Mountain Pine Beetle ◽  
Sedimentary Basins ◽  
Hydrocarbon Exploration ◽  
South Central ◽  
Technological Advances ◽  
Exploration Risk ◽  
History Of ◽  
Geophysical Imaging ◽  
Glacial Cover

The south-central Intermontane belt of British Columbia has a complex architecture comprising late Paleozoic to Mesozoic volcanic and plutonic arc magmatic suites, marine and nonmarine clastic basins, high-grade metamorphic complexes, and accretionary rocks. Jurassic and Cretaceous clastic basins within this framework contain stratigraphy with hydrocarbon potential. The geology is complicated by Cretaceous to Eocene deformation, dismemberment, and dislocation. The Eocene to Neogene history of the southern Intermontane belt is dominated by non-arc volcanism, followed by Pleistocene to Recent glaciation. The volcanic and glacial cover makes this a difficult region to explore for resources. Much recent work has involved re-evaluating the challenges that the overlying volcanic cover has historically presented to geophysical imaging of the sedimentary rocks in this region in light of technological advances in geophysical data collection and analysis. This paper summarizes the lithological and stratigraphic framework of the region, with emphasis on description of the sedimentary units that have been the targets of hydrocarbon exploration.

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