Abstract Computer stratigraphic simulation models provide a quantitative means to evaluate and understand complex interactions of sedimentary depositional systems. People in the geosciences are quickly advancing in their ability to acquire and interpret large data sets, resulting in major advances in understanding earth systems. Simulation is a natural outcome of these advances, as is the need to integrate and process this information. This volume provides a collection of 26 papers that describe and illustrate the application of some of the latest approaches to stratigraphic-sedimentologic modeling. This paper serves as an overview of these papers, classifies modeling, reviews current issues of modeling, and evaluates possible future modeling directions and opportunities. We have recognized several different approaches to modeling and present a rational classification for these model types, illustrated here and in the volume by diverse examples. Despite varying philosophies and methodologies of their creators, most models consist of three essential components: (1) input, (2) engine, and (3) output. Our results suggest that models have a sound observational basis (input) and logical foundation (engine), both of which use ever-improving quantitative knowledge of geologic systems. Roles of modeling include: (1) encouraging accuracy and precision in data collection and process interpretation (Slingerland et al., 1994); (2) providing a means to quantitatively test interpretations of the roles of various driving mechanisms to produce sedimentary packages; (3) predicting or extrapolating results into areas of limited control; (4) affording mechanisms for enhanced multidisciplinary integration and communication; (5) gaining new insights to offer nonintuitive results regarding the interaction of parameters; and (6) helping focus future studies to resolve specific problems. The future of modeling is dependent upon fully using improved computational methods and machines, refining quantitative geologic observations and interpretations, and developing rigorous, quantitative approaches to testing, calibrating, verifying, and comparing models.

Abstract This document provides a record of the discussions conducted by the Geological Observations and Parameterizations (GOP) group, which sought to define and address important questions concerning the parameterization of geological observations for use in stratigraphic simulations. The discussions of this group, which was intermittently composed of a combination of model-building, model-using, and nonmodeling geologists, centered on the type and quality of common geological observations, the scales of these observations, and the accurate representation of observations in geological models. The underlying concerns were whether all relevant processes are accounted for in existing models, and whether modelers are using the available models correctly, inputting realistic values and ranges of values at the proper scales. Our fundamental questions include the following: How closely is the variability of geological observations reflected in stratigraphic models? If such variability is well represented within a model, how well does a simulation predict away from points of control? If it does not do this well, is it the input parameters that are not reflecting the natural variability of the system, or does the fault lie with the model itself? If the model itself is the limiting factor, how well do we really need to constrain input parameters? How well do we understand the nonlinear characteristics of natural systems, and how are these characteristics introduced into models?

Abstract The purpose of inversion is to determine the limits of prediction for model testing and risk assessment given the state of our knowledge (knowledge in the form of model assumptions, accuracy, and precision, and in the form of data distributions, types, accuracy, and precision). Inversion is a tool for making decisions. Should we do inversion? Are current models and assumptions sufficient to solve posed problems, or do we need to develop a new model? Are currently available data sufficient, or do we need to collect more or different data? And how do we decide? The above plethora of queries arose during the committee discussions as general concerns, as did a large number of more specific questions. We record in Appendix 1 all of the questions that arose because the committee deliberations did not allow time for complete resolution of all issues. We recorded all of the questions in the hope that some, at least, will be answered in the future. The question list of Appendix 1 is far too long to address in detail, so the committee focused on attempts to provide some pragmatic rules of operation to guide the actual technical use of inverse modeling. Although the rules set down in this paper are not a universal panacea, they do represent considerable practical experience with inverse models. As such, they are useful guides as one struggles to determine the strengths and weaknesses of inverse modeling.

Abstract A procedure determines the relative importance of uncertainties in input information and in multiple parameter estimation to all outputs from two-dimensional basin modeling codes. The procedure does not rely on Monte Carlo methods, but on some simple properties of the cumulative probability distribution of output variations related to uncertainties. As a consequence, only a couple of computer trials are needed to evaluate the relationship of the variability of outputs to input uncertainties. The procedure is applied to a two-dimensional cross section with evolution of the section with time. Attention is focused first on mainly geologic input uncertainties, and then on uncertainties of thermal factors and of hydrocarbon kinetic factors. Each group is initially taken separately, and then all three groups of uncertainties are combined and used simultaneously. The influence of each group of uncertainties on a suite of different outputs from the basin model is explored at different times across the evolving section. At each lime step, the relative sensitivity is examined of the uncertainty in a specified output to each group of input uncertainties, as is the relative importance of the uncertainty in a specified input to the suite of all outputs at each time step. In addition, the global relative importance of input uncertainties to output variabilities is considered, thereby providing a measure of output uncertainty effects, no matter where and when they occur, as a consequence of input uncertainties. This work enables one to assess which inputs need to be more tightly constrained, and also to determine by how large a factor they need to be better constrained if the uncertainties on a suite of specified outputs are to remain within given tolerance limits. The advantage to this rapid procedure is that one can focus more quickly on those factors of dominance in controlling, say overpressure development or hydrocarbon charge in a basin, without having to spend an inordinate amount of time, effort, or financial or staff resources on providing narrower limits of uncertainty to those input factors that provide but little change in output uncertainties.

Abstract Stratigraphic inversion is a quantitative technique that extracts values of process parameters, such as tectonic movement, lithosphere strength, sea level change, sediment supply, and basin topography, from stratigraphic data. A stratigraphic inverse model contains (1) a forward model that simulates stratigraphy through the operation of a set of input process parameters and algorithms that describe the behavior of the stratigraphic process-response system; (2) a set of observed data that are comparable in type and form to forward model predictions; and (3) a set of equations and algorithms that compare the values of forward model predictions with observations, and simultaneously adjust values of all forward model parameters to create a better match between predictions and observations. The inverse model iteratively reduces differences between forward model predictions and observations until a best match is achieved. The model calculates the degree of accuracy and uncertainty of values of stratigraphic predictions. Constructing an inverse model requires the following steps: (1) selecting a stratigraphic forward model; (2) designing simple mathematical functions that most accurately describe the real stratigraphic processes that operated in a basin and that make inversion computationally possible; (3) measuring data that correspond in type to the output of that forward model and transcribing those data into the form of a numerical vector; (4) selecting an appropriate parameter optimization algorithm; and (5) building a stratigraphic inverse model that connects components of steps 1–4. One purpose of stratigraphic inverse modeling is predicting stratigraphic attributes (e.g., facies, geometry, distribution, volume) with calculated estimates of accuracy and uncertainty. Once the range of parameter values is calculated by the inverse model, a population of forward models may be run that should contain the true stratigraphy. The population of forward models is used to predict the geographic and stratigraphic positions and extent of potential reservoir and source and seal rocks. We show an example of accurate stratigraphic predictions using inverse modeling of the Mesa Verde Group, San Juan basin, Colorado and New Mexico, United States.

Abstract Stratigraphic modeling involves a multidimensional parameter fitting problem where a large number of free model parameters have to be adjusted for the model to match observational data. This task can be viewed as an optimization problem, which here is addressed using a genetic algorithm. The iterative trying-and-checking process, usually done manually, is thereby automated. We apply this method for the automatic construction of sea level and subsidence curves for two simple toy models. We also address the problem of distinguishing the sea level variations vs. subsidence variations, and we give an example of a simulation involving carbonates from Mallorca, Spain.

Abstract Numerical-statistical algorithms are used to model end-member grain-size distributions of pelagic and hemipelagic siliciclastic sediments of the Arabian Sea. The grain-size distributions of sediments from the Oman continental slope, the Owen Ridge, the Pakistan continental slope, and the Indus Fan can be adequately described as mixtures of three end members. The spatial variation in relative contribution of the end members is interpreted in terms of transport processes and provenance. In the western Arabian Sea, deposition is dominated by two end members that represent "proximal" and "distal" eolian dust. A third end member, which dominates the deposits of the middle Indus Fan, represents fluvial mud deposited from low-density turbidity currents (lutite flows). At any given location, the temporal changes in the relative contribution of the end members can be interpreted in terms of climate change. The ratio of contributions of the two eolian end members (i.e., the grain-size distribution of the eolian dust) on the Owen Ridge (NIOP492) reflects the strength of the summer monsoon. Deposition on the upper Indus Fan (NIOP458) is dominated by "distal" eolian dust and fluvial mud. The ratio of contributions of eolian and fluvial sediment reflects continental aridity. The ratio of contributions of the two eolian end members (i.e., the grain-size distribution of the eolian dust) on the upper Indus Fan reflects the strength of the winter monsoon. Our reconstruction of the late Quaternary variations in Arabian Sea monsoon climate corresponds well with interpretations of the loess-paleosol sequences on the Chinese Loess Plateau. In both areas, the bulk of the annual precipitation is confined to the summer monsoon season. Intensification of the summer monsoon during interglacials, which has been identified as the principal control on pedogenesis on the Loess Plateau, also explains increased discharge of Indus River-derived muds to the northern Arabian Sea. Independent evidence for summer monsoon strength, provided by the eolian grain-size record of the western Arabian Sea, fully supports this conclusion. The strength of the summer monsoon thus provides an aridity forcing mechanism for both the Arabian Sea and the Loess Plateau. The grain size of the eolian dust in the northern Arabian Sea and on the Loess Plateau indicates intensified winter monsoons during glacials.

Abstract A stratigraphic simulator called phil. (Process- and History- Integrated Layers) documented the history of a seismically defined cross section through the Baltimore Canyon Trough, offshore New Jersey. This cross section helps to constrain a sea level curve from 30 Ma to the present. The interval from 18 to 11 Ma is especially well defined and is considered a type section for this time interval. The stratigraphy was modeled with empirically derived algorithms that produced a resulting distribution of sediment that were compared at 2980 points along depth converted horizons. The result deviated by an average of 36 m from the observed depths and explains 90.6% of the total variation in depth. This was accomplished by introducing a predominantly siliciclastic sediment supply that was distributed by a mixture of traction and suspension sedimentation processes that varied through time. The traction and suspension mixture varied as the distance to the fluvial source varied with respect to the section. Although the Haq et al. (1988) curve served as a good initial sea level history, it proved to have problems when it was applied to reproducing a stratigraphic record for this section, as well as other sections of equivalent age from North America, Southeast Asia, and Africa. The long-term trends tended to be highly over exaggerated. phtl allowed us to produce a new curve that significantly improves the match between the stratigraphy and the model. phil simulation results allow us to extend the understanding of this cross section by predicting lithofacies distributions and associated physical properties, and systems tract boundaries. The resulting physical properties were used as input to a seismic model. Simulation provides values for tectonic subsidence and sedimentation supply rates, carbonate production rates, definition of stability conditions, erosion rates, and the development of water level history that integrates all the active processes. Simulation also is an important tool for visualizing the development of structural and stratigraphic features.

Abstract Observations of modern and ancient sedimentary basins indicate that the shoreface and the depositional shelf break (DSB) can range from coincident to more than 100 km apart. Most conceptual and numerical models of sequence formation do not adequately separate these two features. The model used here incorporates independent calculation of the position of both the shoreface and the DSB; however, at present the lack of an adequate understanding of long-term shoreline response to sea level and other environmental change is a serious limitation to our understanding of the genesis of continental margin stratigraphy. When independent movements of the shoreface and the depositional shelf break were incorporated into the model, both ravinement surfaces and regressive surfaces of erosion developed in the simulations. This response attests to the importance of distinguishing these two features and to the important role of the physiographic break at the shoreface. In model results, the shoreface and DSB do not always respond similarly to sea level fluctuations. The relationship between shoreface and DSB movements differs depending upon whether they are geographically separated. As a result, defining sequence boundaries and systems tracts can be difficult. The extent of the transgressive systems tract, in particular, is a problem because progradation of the DSB begins partway through the shoreline transgression. This mismatch between the shoreface and DSB predicted by the model has not previously been noted. Fluvial erosion of the coastal plain develops progressively as the shoreface advances, indicating a progressive development of the sequence boundary. Onlap onto the front of the previous regressive shorefaces occurs primarily during the transgressive systems tract. Systems tracts therefore should be based on stratigraphic and lithological distinctions in the rock record, and not be tied to an interpretive model. To accurately calculate vertical motions and resultant stratigraphy for high-frequency eustatic fluctuations, isostatic adjustment and erosion to an equilibrium profile are modeled as time-dependent processes. These models show that the form of sequences changes with the frequency of eustatic fluctuations. Similarly, the erosion rate has a major influence on stratal relationships. The rate of isostatic compensation can alter whether a sea level cycle generates a sharp-based or gradational-based shoreface. The type of base at prograding shoreface successions can change within sequences. Thus, the sequence boundary should be placed at the top of regressive shoreface packages. Continued isostatic or compactional subsidence following the deposition of depositional delta lobes can explain the formation of flooding surfaces and parasequences.

Abstract Although quantitative stratigraphic models have been able to reproduce the gross characteristics of sedimentary successions, most are less successful at reproducing fine stratigraphic details such as marine erosion surfaces, and yield little insight into the dynamics of sediment transport. We have developed a new two-dimensional stratigraphic model that combines a geodynamical model that simulates tectonics, isostasy, compaction, and coastal plain erosion and deposition with a morphodynamical model that simulates marine sediment transport. The morphodynamical model differs from sediment-transport models used in older stratigraphic models in that it allows for both offshore and onshore transport through an estimate of long-term advective and diffusive sediment fluxes, and applies concepts of dynamic equilibrium to the shoreface and continental shelf. This more sophisticated sediment-transport model allows us to simulate the response of stratal geometries and surfaces to changes in hydrodynamic climate, as well as to changes in sea level, tectonics, and sediment supply. In this paper, we simulate a narrow, steep continental margin with relatively high sediment supply (similar to the modem northern California margin) that is undergoing high-amplitude (80 m), high-frequency (40 k.y.) sea level fluctuations. We then compare the effect of varying several parameters on the resulting simulation. These sensitivity tests illustrate the effects of variations in the steepness and erosion rate of the coastal plain, hydrodynamic intensity, and disequilibrium initial conditions, and also a nonsinusoidal "asymmetrical sawtooth" eustatic curve approximately reflecting sea level change over the past 125 k.y. Although quantitative calibration of the model against real hydrodynamic data has not yet been completed, the model responds to changes in input parameters that appear realistic and offers a possible explanation of the patterns observed in real sedimentary successions. Marine and subaerial erosion surfaces are produced at logical times during a sea level cycle, and the shoreface shape changes in ways that resemble real profile adjustments to changes in rates of sea level change, sediment supply, and hydrodynamics. Model results suggest that sediment-transport processes may strongly overprint the stratigraphic record, allowing a considerable variety of sedimentary styles to be produced with identical sea level, tectonic, and sediment-supply histories. In the simulations, sequence thickness and the location and preservation of transgressive and regressive deposits vary with changes in coastal plain behavior and wave intensity. Steeper coastal plains result in reduced subaerial erosion and better shelf preservation. Low rates of subaerial erosion or high wave intensity results in thick, steeply inclined regressive deposits, but poor preservation of transggessive deposits; thicker shelf sections are not necessarily more complete. Clinoforms develop within the model only under conditions of significant disequilibrium; such conditions could occur in nature due to changes in relative sea level that are large relative to rates of sediment supply. These results suggest that factors other than sea level, amount of sediment supply, and tectonics are significant in stratigraphic development and highlight the need for the inclusion of more rigorous sediment-transport dynamics in numerical and conceptual stratigraphic models.

Abstract The shoreface translation model (STM) incorporates advances in the theory for coastal responses to changes in relative sea level, exposing some well-entrenched misconceptions about the formation of transgressive and regressive strata at chronosomal scales. The STM is a mass-conserving, morphological-behavior model that provides added generality to the updated theory by allowing for open sediment budgets (on the shoreface and in the lagoon) and time-dependent changes in shoreface and barrier geometries. Both the theoretical basis and application of the STM give neutral transgression for balanced sediment budgets on gently sloping surfaces undergoing a marine transgression. Under these conditions, no transgressive strata are formed, and the land surface being transgressed is not disturbed en masse. Consequently, shoreface-ravinement surfaces are not necessarily inherent by-products of transgression as assumed previously. Simulated transgressive strata are laid down (aggradational transgressions) only if there is a positive net littoral sediment supply (from deltaic sources or erosion of shoreline promontories), significant deposition in the lagoon (due to trapping of fine marine sediments or direct fluvial inputs), or both. Shoreface-ravinement surfaces are produced only under conditions of negative littoral sediment budgets or if the land surface being transgressed is steeper than the shoreface (degradational transgressions). For negative sediment budgets, simulated shoreface ravinements form on low-gradient surfaces without seaward sediment displacement or genetically related aggradation of the seabed farther offshore. Ravinements also can develop during progressive deepening of the shoreface during transgression and highstands. Simulated highstand ravinements are consistent with, and provide an alternative explanation for, coarse-sand lags found on the lower shoreface of many accommodation-dominated shelves today. Simulated forced regression results in massive in-situ reworking of the highstand shelf surface, inevitably producing a strandplain stratum characterized by (1) an unconformity at its base and (2) shoreface isochrons, as opposed to the landward-dipping, backbarrier isochrons that characterize transgressive barriers (which consist of washover and tidal-delta sand deposits). The revised approach to simulating each of these intrachronosomal-forming processes has significance for sequence models and the interpretation of stratigraphic data at basin-fill scales.

Abstract A numerical model has been developed to investigale the grain size distributions and stratal patterns associated with compressional and extensional fault-related folds in nonmarine settings. First, the basic predicted stratal and facies geometries for a single extensional and thrust-fault-related fold are identified. Then the modeling is extended to situations involving multiple faults and changes in displacement velocity. Finally, the model is invoked to study structural inversion comprising a change from extension to compression. The stratigraphic architecture of facies patterns predicted by the model is sensitive to convergence and sequence of fault activation and may serve as a guide in interpreting the stratigraphic record associated with multiple fault structures. Application of insights from our modeling to a few natural examples of growth faults and sheds light on various interpretations of these structures.

Abstract A three-dimensional (3-D) forward stratigraphic model has been built to simulate geometries and lithologies of coastal environments (e.g., coastal plain, shoreface, and upper offshore) on time and spatial macroscopic scales (hundreds of thousands to tens of millions of years, and tens to hundreds of kilometers). The model is based on fluid-flow mechanic laws. A generalized diffusion equation, taking into account water discharge, simulates fluvial- and gravity-dominated sediment transport. Sediment load carried by water is proportional to the basin slope (moving force), water discharge (water transport capacity), lithology fraction (sediment availability), and diffusivity coefficient (transport efficiency). A 3-D theoretical fluvial-dominated delta was simulated to test the geological consistency of the model. Although the model is based only on sediment transport laws, the parameters of which are assumed constant in this theoretical example, it reproduced correctly sequence stratigraphy concepts such as formation of genetic units, volumetric partitioning, and facies differentiation due to sea level variation. Simulation of the Lower Cretaceous formation of the Paris basin (France) was done at a basin scale (basin size: 200 × 240 km 2 ; formation duration: 10 m.y.) to fit the simulation outputs on well data. An inversion loop was used to quantify model parameters such as accommodation map, water and sediment supplies, carbonate growth law, and diffusivity coefficient. Sediment thickness was quantified with an error of less than 1 m at the 12 wells used during the inversion loop, and less than 10 m at 25 km from these wells. These applications validate the geological consistency of the general physical principles used in the model. This 3-D improved diffusive model helps to determine an average geometry of sedimentary units and to characterize the facies content (depositional water depth, sand:shale:carbonate ratio) inside each of them. The model provides a quantitative tool for better understanding the 3-D stratigraphy of sedimentary basins.0

Abstract Determination of the transport ("diffusion") coefficient, the main parameter of most forward models for generating fluvial stratigraphy, requires finding the average slope required to transport the total sediment load delivered to a given point for a given water discharge. Finding this value, in turn, requires averaging the substantial fine-scale local variability in transport capacity that one encounters in most natural rivers. The problem is especially acute for braided rivers, in which the local capacity varies strongly in time and space as channels migrate, flow shifts from one part of the channel network to another, and confluences, which account for a disproportionate share of sediment flux, form and dissipate. Here, we present a model for computing spatially averaged sediment flux in a sandy braided river system. Coupled with sediment mass balance, the sediment-flux model leads to the usual diffusion equation for surface topography. The problem of indeterminacy of channel width is dealt with by using an empirical constant value of 1.8 for the mean nondimensional (Shields) stress. We test the model by applying it to a mine-tailings fan in which all independent parameters (sediment flux, water flux, grain size, deposition pattern) are well known and constant. The statistical parameters needed to determine the transport coefficient are determined from independent measurements of the river network on the fan. Using these inputs, the model predicts the fan topography well. The model suggests that, for a highly active braided system such as this one, the effect of the fluctuations in sediment flux can increase total sediment flux by a factor of two to four relative to what would be predicted from mean values alone. The data also suggest, however, that some of the key statistical parameters vary significantly downstream along the fan. This variation may result from downstream variation in grain-size distribution, sediment flux, or both.

Abstract Future naval engagements require a thorough scientific understanding of the waters and sediments found close to our continents. Properties of the sea floor overlying our continental shelves and slopes bear directly on the tactics and operations of modern navies. Numerical simulations of the sediment dynamics and stratigraphic evolution of marginal seas are needed to fuse information from the atmosphere, ocean, and regional geology. These automated predictions can populate digital databases in areas and times for which actual measurements are not available, or for which purely statistical estimates are not adequate by themselves. A numerical family of models is described, able to simulate the delivery of sediments and their accumulation on continental margins over time scales of tens to thousands of years. Model predictions include the effects of sea level fluctuations, river floods, ocean storms, and other relevant environmental factors (climate trends, random catastrophic events), and work at a time step (daily) that is sensitive to short-term variations of the sea floor. Nine numerical models are described in terms of their intermodel linkages, data needs, constitutive equations, numerical output, and verification. Together, the models are able to simulate river discharge delivering a multisized sediment load onto and across a continental margin, including sediment redistribution by (1) river mouth processes, (2) buoyant river plumes and hyperpycnal flows, (3) turbidity currents, (4) currents and waves, and (5) debris flows generated from slope instabilities. The final product is a sea floor described in terms of geotechnical and acoustic properties and associated acoustic processes (e.g., sound reflection).

Abstract Geostatistical reservoir simulations are now common tools used in intensive exploration and reservoir appraisal; however, at this stage of intensive exploration and appraisal, significant uncertainty still exists due to the limited amount of hard data. A way to better constrain these stochastic simulations could be to integrate information coming from a stratigraphic modeling approach. Stratigraphic models give information about geometry, continuity, location, and dimensions of the main depositional sequences in a study area by using input data such as eustasy, subsidence, and sediment supply; however, geostatistical models aim to generate equiprobable images of the reservoirs inside the main sequences, which honor the well data, and whose variability can be linked to the variability computed from the data. This approach has been validated on an outcrop case study in the Campanian of the San Juan basin in Colorado. The IFP (Institut Français du Pétrole) stratigraphic model Dionisos has been used to introduce quantitative sedimentological knowledge in the stochastic reservoir model heresim. The global trend of the sand:shale ratio evolution in the study area also has been taken into account as an external drift in the geostatistical simulations. For this purpose, the usual algorithm in heresim has been extended for nonstationary (sedimentary trends from continental to marine environments) cases by using the facies proportion blocks instead of one single proportion curve. The coupling of both methodologies allows for more geologically constrained images of the reservoir.

Abstract Fuzzy logic, an extension of conventional mathematical logic, provides us with methods that allow for formalization of qualitative information such as "soft" geological knowledge, thereby making it available for numerical treatment on the computer. In addition, fuzzy methods are easy to work with and help in constructing complex models. This usefulness is demonstrated by showing the successive steps in constructing a simple fuzzy system designed to control a stratigraphic simulation model of a section from the Miocene carbonate platform of Mallorca, Spain. In the discussion, I argue that using a collection of fuzzy rules for modeling in principle is no different than using a system of conventional mathematical functions, except that using fuzzy rules is much easier and more effective.

Abstract In this paper, we consider the dynamics of sedimentation in sedimentary basins and apply fractal models to quantify the dynamics of sedimentation and the resulting basin heterogeneity. First we consider porosity variations in sedimentary basins. A stochastic model of deposition and erosion is applied to the spatial and temporal variations in deposition and erosion. The spatial variability of the topography along strike in this model is a Brownian walk. This has been widely observed as the spectral behavior of topography. We show that this variability also is consistent with the spatial distribution of oil pools in sedimentary basins. The temporal variability of sedimentation is associated with the vertical variability of porosity. Vertical well logs have power-law power spectra, S, proportional to approximately k – (3/2) , where k is the wave number. The vertical variability of sedimentation and erosion also can be used to model the completeness of the sedimentary record. The rate of sedimentation, R, has a power-law dependence on the time period of sedimentation, T, with R ∞ T –0.76 . A time series with power spectrum S ( f ) ∞ f –(3/2) , where/is the frequency, gives R ∞ T –0.75 . We also examine the persistence in the series of bed thicknesses as a function of depth. For the model, no persistence is observed. If the model fully characterizes the autocyclic dynamics in sedimentary basins, the lack of persistence in the synthetic bed sequences suggests that observed persistence and cyclicity in real bed-thickness sequences must be the result of allocyclic processes.

Abstract dynased was developed to analyze the complex interaction of nearshore depositional processes, determine the levels of deterministic chaos arising from such relationships, and examine fundamental assumptions made in the process of using computers to model sedimentary systems. dynased consists of three simple, empirically derived equations modeling a single continent surrounded by a depositional basin (Figure 1). Mantle convection is not taken into account in the model; i.e., tectonism, rifting, and subduction are absent. The three coupled state variables used in dynased are hinterland elevation, sea level elevation, and sediment transfer rate. Hinterland elevation varies with changes in sea level elevation and sediment transport rate. Sea level elevation is a function of changes in hinterland elevation and sediment transport rate. Sediment transport rate varies with changes in the difference in hinterland elevation and sea level elevation. The lag, or delay, variables decide the length of time before the system responds to changes in the corresponding state variables. Although dynased is quite simple, 17 variables, consisting of coefficients, exponents, and lag values, are necessary to fully define the system. dynased produces responses that range from cyclic to quasicyclic to chaotic. The output from dynased, expressed as changes to the state variables, commonly is comprised of hierarchical cycles. Most importantly, the cyclicity seen in dynased's responses is not a result of external forcing functions; for example, cyclicity in sedimentary sequences is commonly attributed to the Milankovitch cycle. Cyclicity in dynased state variables and resulting lithologies arises spontaneously due to the inherent interdependencies among process variables in coupled systems of nonlinear equations.