Identification of shallow hazard features at the sub-surface are performed via seismic interpretation of high-resolution three-dimensional (3D) seismic surveys. Today, seismic interpretation is a fastidious and time-consuming process. Usually an interpreter must spend weeks or months to fully interpret this type of survey and its volume. Deep learning methodologies utilizing neural networks are currently revolutionizing seismic interpretation by accelerating the speed in which geologic features such as faults, salt diapirs, and gas chimneys can be mapped. It has become an industry goal to utilize neural networks for all uses of seismic interpretation, including shallow hazard identification. There have been challenges to the adoption of machine learning, to the interpretation of shallow hazards. The results of this interpretation have a direct impact on drilling safety and therefore its accuracy is paramount. Traditional machine learning technologies do not consider the human experience and abstract thinking required for seismic interpretation. For interpreters to fully trust the results of the neural networks, they must spend an extensive amount of time conducting quality control of the results and editing as needed. Traditional machine learning technology requires a significant amount of time to be spent on data preparation. Our project has two main goals. The first goal is to create technological improvements to enable humans to work interactively with neural networks. The second goal is to reduce the amount of time spent in data preparation to zero. We present a new interactive deep learning methodology, that differs from existing methodologies and achieves these two goals. We have built our methodology on top of our proprietary technology that provides random data access to seismic data, enabling interactivity between the neural network and the geoscientists, therefore putting geoscientists in complete control. Our methodology eliminates the burden of data preparation methodologies, because it does not require prior randomization of the seismic data like older technologies. We achieve acceleration, and improved results in the seismic interpretation of shallow hazards.

Offshore Seismic Permanent Reservoir Monitoring (commonly known as PRM) is a seabed-based technology that is becoming part of the reservoir engineer's toolkit in practicing better management of oil and gas fields. In its most commonly practiced form, PRM involves conducting 3D seismic surveys at repeatable time periods, generally somewhere between six months and two years. The time interval between surveys may be variable, and depends on the specifics of the reservoir being monitored. It has been demonstrated to be a technical success because, as fluids are injected and/or produced from a field, the seismic data change in response to the changes in the reservoir. The field implementation of PRM has now become a major geoscience and engineering activity yielding tangible results. This paper is an attempt to present an overview, facts, and opinions that will be of use to engineers and geoscientists who are interested in what has been done, and what may be done, in the use of seismic permanent reservoir monitoring, or oilfield surveillance. The PRM market appears to be on an upswing, but it remains to be seen if that upswing continues. There are several reasons that have tempered the adoption of this technology. Two are being emphasized here. One is that it has been difficult to determine and publicize the cost-effectiveness of PRM. While upfront costs are relatively large compared to many geological and geophysical activities, they are not large when compared to overall field development, optimization, and maintenance costs. Companies are now taking a more realistic look at the ultimate value derived from PRM due to the growing number of published benefits versus cost. The second moderating reason emphasized here is the number of stakeholders, with a wide variety of technical expertise, perspectives, objectives, and motivations, which must be involved in approving and executing such a project. This situation is being addressed as more corporate leaders are made aware of how PRM may address, in addition to production and operational needs, a number of health, safety, and environmental (HSE) concerns, broadening the interested constituent base within operating companies, and further establishing the benefits, both technical and economic, of PRM. There are currently 13 installed PRM projects, with the longest-running (Valhall) having been operating since 2003. The high-quality seismic data obtained from these projects are capable of showing very small changes in seismic amplitude and/or travel time that result from changes in the reservoir and its contents, such as fluid type, saturation, and pressure. The seismic systems themselves have also become the vehicle to integrate other measurements at the seafloor, such as temperature, water chemistry, or small changes in seafloor topography – all parameters that may have HSE implications. The growing importance of this oilfield surveillance approach will ultimately result in a variety of engineers collaborating not only with geoscientists, but also with other departments within the corporation such as Quality and HSE. As shown by the technical and economic successes of at least two projects (Valhall and BC10), the appropriate use of a PRM system significantly increases recovery, production rates, and operational efficiency, and reduces reservoir management costs ( Chen and others, 2015 , Barkved, 2012 , Caldwell, 2009 , Caldwell and others, 2015 ).

Abstract Finding sufficient information to help drive better decisions is not an issue in the oil and gas industry—this industry is one of the most data-intensive in the world. The challenge is interpreting all the data we possess. Furthermore, various disciplines or departments hold critical information that might be useful to others, but not often can it be shared because of technology or process issues or simply because it may not be known that others could make decisions with it. How can asset teams leverage all the information they possess to make better decisions and improve production and recovery rates? In particular, what can be done to bring together the vast amount of information that both the geological and geophysical (G&G) and stimulation worlds have? What is needed is a solution that allows stimulation data to be integrated with geological and geophysical data to understand how the reservoir will fracture and respond to stimulation treatment. This solution will allow for better decisions to be made about how overall reservoir production can be improved: microseismic events can be viewed in context of G&G data to refine stimulation treatments; attributes of seismic information, such as curvatures, can be used to understand how the formation might fracture and help drive well placement and perforation strategies; experts who do not traditionally weigh in on fracture design (i.e., geophysicists) can now have a seat at the table to help improve stimulation placement and treatment design for improving stimulation effectiveness. In new plays, like some of the unconventional shale gas plays, little is often known initially about how the formation will react to a given stimulation treatment. In such cases, a trial-and-error approach is often used; however, a strategy that might have been successful in an older shale play might not be successful in a new shale play, as with traditional sand reservoirs. The ability to use seismic and other data, as well as expertise from other disciplines, might greatly enhance overall success in new areas. Introduction Information is critical to making decisions, but how do we get all of the information we need into the hands of the right people at the right time? How can we create a collaboration environment in which correlations and trends can be visualized and verified? And, more importantly, how do we create a workflow that allows us to continuously optimize results quickly, even in real-time? Nearly every service company and operator has an initiative to drive efficiency by better integrating data and disciplines. Many are steadily making improvements in data access, and this paper presents a software tool for visualizing microseismic events in the context of the geological and geophysical background or geomechanical model of the formation and a workflow to optimize stimulation performance. These steps bring together geoscientists and fracture engineers so that they can make decisions collaboratively and improve the return on stimulation investment. Why, and where, is this important? In tight gas and shale plays, production of a well is dependent on the effectiveness of hydraulic fracture treatments. It is commonly said: " If we do not fracture it, we do not produce it.?? The question then becomes, beyond waiting to realize production, how does an operator know if a formation as been effectively stimulated? Microseismic fracture mapping allows us to visualize the physical location in the formation that was treated, or at least disturbed by the treatment. Fracture mapping removes the guesswork about whether the treatment stayed in zone until actual production numbers are available. Reference 22 provides examples of the benefits of integrating microseismic mapping in the Overton Field of East Texas.

Abstract Visualization technology has changed dramatically over the past few years, moving from a high end tool used on the most expensive projects to a desktop solution applied to significant range of exploration to field development opportunities. Visualization has become a tool both to speed 3D interpretation and integrate multiple geologic and geophysical databases to understand complex geology or work deep poorly imaged structures. The rapid change in adoption is being driven by the constant requirements for cost reduction and cycle time improvement. This paper will focus on a small number of technical workflows and demonstrate how visualization can play a vital role in improving the quality of the interpretation and provide new insights into the data. The workflows will also highlight that further productivity gains are still achievable as new hardware and software expands our outlook of what is possible with visualization. Introduction Interpretation Workstations originated as a tool to digitally capture what was once a laborious process of using a time-stick, to manually measure seismic horizon 2-way time, which was then posted to a map for hand contouring. The innovation was to us the workstation, to digitally post data with drafting software or to grid and map the data with the company's mainframe computer. The advent of workstations coincided with the first 3D surveys, and was seen as a way to organize the large new datasets into a virtual library of 2D lines in x and y directions. Workstations took the two dimensional paper seismic line into a computer version ready to be worked by the geophysicist. As seismic interpretation software, workstations, and data evolved into the present sophisticated computing and advanced imaging of today, many mainstream interpreters continued with the traditional line by line, two-dimensional workflows which, date back to paper sections. Only today traditionalists use high-end Linux workstations to display the map and seismic line. Visualization Interpretation software is as large a step change as the move from paper to workstation. The adopters of this new technology have a competitive edge in the challenging exploration environment of today. Visualization technology now enables interpreters to interact with multiple 3D volumes. Workflows for seismic volume interpretation are facilitated by auto-trackers and wavelet based propagation tools. The volume interpreter can validate his automated interpretations rapidly by driving through the seismic volume, stopping as needed to correct auto-interpretation busts. The volume interpreter can quickly generate surfaces and dip attributes to visually identify areas where his interpretation is geologically incorrect and then make immediate data based, interpretative decisions to correct his propagated horizons. With volume based fault interpretation there is immediate feedback in the form of auto-correlated fault surfaces. Interpretation errors are quickly recognized on auto-correlated fault planes when surfaces become non-geologic. Instant fault plane tessellation means that the interpreter recognizes a correlation bust or poor fault pick as soon as it is made, and can make immediate corrections. Visualization technology is now however, moving beyond 3D seismic interpretation into a true 3-dimenstional geologic interpretation platform. Multiple arrays of data from 2D and 3D seismic to georeferenced surface geologic maps, cross sections, core, and dipmeter, to EM data can be displayed in true vertical and geographic 3-dimensional context. This context is scale independent and can be used from the basin scale new venture context to field development for geosteering a horizontal well. In today's competitive landscape, traditional interpreters are outmatched by those using visualization technologies.

The key to unlocking innovation in the Upstream is standards. WHAT!? Does this sound backwards and non-intuitive? Don't we usually associate innovation with free-wheeling, no-boundaries kinds of approaches? How can people feel free to innovate if you tell them to "do it this way"? Well, it all depends on where you think the value comes from. Technical computing in the Upstream oil and gas industry has evolved into extremely powerful, yet extremely complex systems. Varied and coagulated connectivity networks underlie a myriad of platforms, from UNIX to PC to mainframes to supercomputers...to server farms, to thin clients and Blackberries, etc. At the other end of these systems, a multitude of user interfaces become the most visible aspect of these complexities to the user community. At the center of such complex technical computing system are the varieties of software applications: geoscience, engineering, operations, business, personal productivity, and IT, etc...usually supplemented out of necessity by a veritable foundry of line-coded "tools", "agents", or "macros". This software or line code is written by one of, or all of, several million developers, sometimes including end users themselves, in many different "languages". The fuel and lifeblood for this technical computing system is data. This data comes in a million different formats, sizes, and shapes. It comes in logarithmically increasing volumes...in numbers making "a million" seem like a quaint and archaic term. With the complications of these various elements and their inter-relationships in the systems, complexity has become the enemy of innovation. Too many engineers, geoscientists, field operators, accountants, and managers (not to mention IT specialists, and others) spend too much time dealing with the complexity and moving parts of the "system"...and so far too little time evaluating, analyzing, sciencing (is that a word?) and innovating in the environment. While there are many targets for simplification in these technical computing systems, DATA rises to the top of the list as the most critical element. In this upstream environment, data is at the core of the systems - resting upon the networked infrastructure, and feeding the applications and user interfaces. Data is what the systems were built for and around. After all, scientific software applications without data are, in essence, just theory. And, I don't need computer infrastructure if I don't have any data or even software without data. Data is king. Yet data is probably in the worst shape of all the elements of the system in terms of its wild, complex nature. Historically, geoscience based UNIX systems have involved large data file sizes (think seismic). Engineering and business productivity systems have grown from environments with relatively small data file size, but with numerically many more files. While the systems continue to evolve and converge, the Upstream industry is faced with a tidal wave of information; 2-D becomes 3-D, now 4-D seismic. Real-time data capture systems and others have led to an explosive exponential growth in data volumes and storage requirements. This reality has placed the technical user in the proverbial needle in the haystack situation. Another reality of this information overload environment is that all data is not created equal. Some data have greater importance than others. Imagine looking for that needle in not just one haystack, but a field of haystacks. Maintaining data quality will require progressively better automation as data has entropy, always seeking a lower state.

Abstract As the world enters the new millennium, many questions are being raised about energy supply and demand. Although various new sources of energy are being introduced to satisfy future global needs, it is expected that at least for the next twenty years petroleum will still be the dominant fuel. The question then becomes "What human and technical resources will be required to meet the world's oil and gas needs over the next couple of decades" The manpower pipeline upon which the industry has relied over the last 100 years to supply new technologists is no longer capable of delivering the geoscientists and engineers that the oil business has required in the past. Other opportunities, particularly in the environmental arena, have aggravated the situation for petroleum by enticing future reservoir engineers, geologists, etc. to pursue non-petroleum careers. An offset to this future manpower struggle is the industry's ability to develop technologies which hopefully will make technologists more productive and effective. Some of these new and emerging technologies will be discussed as well as the human characteristics and skill sets which will be critical in reservoir technologists of the future. Introduction According to an American Geological Institute estimate, 1 of the seven trillion barrels of potential global resources, only twenty-five percent has been produced or booked as proven. This means that approximately three-quarters of the world's potential resources are either yet to be discovered or are currently considered non-producible. With demand for petroleum expected to increase to over 100 MMBOEPD by the year 2020, 2 the petroleum industry will continue to be called upon to provide the human and technical resources to ensure there are no interruptions in supply. In the past the industry has risen to similar challenges through technical innovation and aggressive recruiting. However, over the past twenty years, there has been so much turmoil in the industry due to wild oil price fluctuations and the resulting restructuring of most petroleum employers that many of the traditional sources of reservoir engineers and geoscientists have radically been reduced or eliminated altogether. This paper addresses one question. Will the industry experience a shortfall in reservoir engineers and geoscientists over the next few years? If so, what technologies and processes are being pursued and/or implemented to offset the shortage of the personnel who are responsible for the characterization of existing, newly discovered, or to be discovered reservoirs? Manpower Trends Figure 1 graphically illustrates the impact of crude oil prices on manpower level in the petroleum business over the past sixty years. 3 The correlation is very good overall with a slight lag in the manpower curve occurring after the 1981 price aberration.

Abstract Time-to-depth conversion procedures are being used to enhance the structural signature of complex geological features on seismic sections. It is important to separate the effects that arise from actual geological structure from those created by a particular numerical algorithm used to build the depth/velocity model. The accuracy of the numerical model i influenced by the quantity of well control incorporated into the time-to-depth conversion procedure. The velocity models based on different amounts of information coming from seismic signal processing and well-control data are applied to the same dataset. The results are then compared to determine the effects of the mathematical interpolation and calibration procedures in the time-to-depth conversion. The improvement in accuracy of a particular numerical model by incorporating time-depth tables that have been synthetically generated from available well log data is discussed. The fast and effective workflow allows an geoscientist to produce depth-converted maps of large project areas quickly and easily. Some aspects of understanding a compromise between accuracy and computational costs using various depth conversion methods are discussed. An increase in model accuracy by using more advanced but more computationally intensive depth conversion and velocity extraction techniques may play an important role in reducing prospect risk beneath complex geological structures, such as salt domes. The examples of accuracy increase fo complex geological structure imaging through implementing more advanced algorithms are present. The effectiveness of two workflows is compared for different geological scenarios. The depth model validation through available 3D ray tracing simulation is considered. Introduction Seismic data represent the temporal records of acoustic signal on a surface where a receiving system is mount. In the past, the processed seismic data were interpreted in time. Of course, the main goal of seismic exploration is to create the image of undersurface Earth layers in depth that gets really critical fo planning drilling projects. The depth converted seismic data also provide an enhancement of the structural signatures of complex geological structures. Modern seismic processing methods offer different solutions for accomplishing depth-conversion goals from vertical stretch techniques to prestack depth migration. 1–5 A choice of depth-conversion workflow depends on many factors, including the required depthconversion accuracy, the quality and type of data available, deadlines, computer time constraints, the complexity of geological site and so on. In the paper we will consider different approaches for depth conversion. We will demonstrate an opportunity of increasing accuracy of the depth-conversion method by optimally incorporating well control and seismic data. We will also address the issues of depth model validation using 3-d ray tracing that helps an geoscientist to identify areas where a particular algorithm introduces unacceptable errors on the depth surfaces, so one should proceed towards using the more advanced velocit analysis technique and depth-conversion workflow to increase the model accuracy.

Abstract Voxel technology has recently become widely available to geoscientists in the form of advanced 3D seismic interpretation software. This paper discusses the power of this relatively new technology which potentially allows a step change in the speed with which 3D seismic data can be interpreted. In addition, powerful new analytical functionality is now available which for example allows amplitude connectivity to be very quickly evaluated, and more than one 3D survey to be interpreted at the same time. The objective of the paper is to encourage geoscientists to use voxel technology to assist in the interpretation of 3D seismic data. The value of much faster, and more robust 3D seismic interpretation is clearly linked to the business drive for faster seismic cycle times, and accelerated exploration and field development and production. Introduction Voxel technology has recently become widely available to geoscientists in the form of advanced 3D seismic interpretation software. Several vendors market voxel based interpretation systems either as standalone applications, or as part of their integrated interpretation platforms. 3D seismic interpretation turnaround time Voxel technology differs from that used in conventional workstation design, in that all the seismic trace data is stored in memory (RAM). This leads to a step change in speed in terms of data access time which has a corresponding very positive impact on the time that it takes to interpret a 3D seismic dataset. Faster 3D seismic interpretation is clearly linked to the business drive for faster seismic cycle times, and accelerated exploration, and field development and production. 3D seismic interpretation'in real 3D' A further benefit of using Voxel based software to interpret 3D seismic data is that it is possible to interpret the data 'in real 3D'. Instead of interpreting in lines, crosslines and timeslices from a 3D seismic dataset, it is now possible to display and interpret a complete 3D seismic cube on a workstation screen in 3D. This has major benefits in allowing the interpretation and visualization of 3D seismic data in a way that results in a much faster understanding of the geological significance of the dataset. Although voxel based interpretation systems were initially considered to only work well in good data areas, and where reservoirs and/or hydrocarbons are represented by amplitude anomalies, we now conclude that they are equally useful in poor dilta qualily areas. The ability to animate, or pan through, any dataset in real-time can allow the identification of subtle features which might otherwise have been overlooked. Such techniques also allow more confidence to be established in the interpretation of poorer quality datasets, by for example animating through 'squash' volumes. Connectivity analysis and 'sculpting' Voxel based interpretation systems are particularly well suitedfor analyzing the connectivity of seismic amplitude anomalies. This works particularly well on acoustic impedance datasets where a reservoir is well resolved, for example as a high porosity acoustic impedance trough. Voxel technology also allows 3D seismic volumes to be 'sculpted'. For example, a top and base reservoir interpretation can be used to 'sculpt out' the seismic between the top and base reservoir.

Abstract Today, most E & P research makes use of large, three dimensional data volumes to model, simulate and solve real world problems. This is especially evident when working with reservoir characterization and simulation data. Increasingly, there are problems that require up to many terabytes of data per run. Data sizes are increasing by orders of magnitude as teraflop scalable supercomputers become available as standard E & P machines. As a scalable supercomputing resource, these systems can be configured to meet computing needs ranging from the smallest to the largest, most complex and demanding reservoir problem. In the past few years, the cost of supercomputing technology has decreased while the performance has increased. This has allowed E & P companies to deploy this type of technology throughout their organization in places never before possible. For example, it is now possible to accommodate remote sites with smaller supercomputer systems and central engineering sites with larger systems. This enables cost control, while providing supercomputing resources at the locations where they are needed the most. Scalability includes adding computing resources as required: more parallel inputloutput (UO) with faster I/O performance, more parallel processing units for compute intensive problems. large distributed shared memories for terabyte size data sets and high-performance graphics visualization. Highly scalable supercomputers can beused as a tool to better predict the behavior of the reservoir and produce more oil and gas from known reserves. With unprecedented graphics and computing power, these machines compute and visualize the complex relationships among parameters that must be considered before. during, and after a simulation run. This visual data integration enables users to better understandthe relationships among fluid and rock properties within the reservoir, both before and after simulation. Users are able to optimize simulation time by making decisions based on a more complete and thorough understanding of data through visualization. This paper will show how innovations in high performance computing and visualization can benefit work inreservoir characterization by discussing these significant shifts in computing technology. 1.0 Innovations In Computer Architecture A common requirement throughout the industry is to be able to collect and process large data volumes that will result into a realistic representation of the sub-surface. It is becoming more common for geoscientists to visualize datasets that are a gigabyte in size while some companies are now requesting for methods to process and selectively visualize terabyte size data sets, Innovations which allow this type of processing and visualization to occur are inherent in the design of the Scalable Shared-Memory Multiprocessor (S2MP) system architecture. Figure 1. Shows the S2MP architecture which utilizes the following features: Distributed Shared-Memory and I/O System Interconnections Directory-based Cache Coherence Page Migration and Replication Distributed shared-memory (DSM) and I/O : S2MP memory is physically dispersed throughout the system for faster processor access. Although main memory is distributed, it is universally accessible and shared between all the processors in the system. Similarly. I/O devices are distributed among the nodes, and each device is accessible to every processor in the system.

ABSTRACT The recent discoveries in the subsalt trend Offshore Louisiana are examples of how teamwork And technology can open up a new frontier in a maturely explored basin. Several key relationships had to succeed before the subsalt plan could become reality: Partnerships between companies with different experience, expertise and viewpoint; Regional understanding of the basin geology coupled with a detailed understanding of salt tectonics; Integrated teams of engineers, geoscientists, and other specialists to handle new drilling problems; Proper application of new seismic imaging technology; and Support for key research, both internal and external. Electively managing these relationships has helped the risk/reward balance, allowing the subsalt to be an economic venture. The high entry cost of subsalt wells, basin-wide 2D and 3D seismic databases, and the technologies employed (such as 3D depth migration), would be prohibitive without the possibility of significant discoveries and large reserves. Also, the challenge of managing such diverse talents and personalities involved with the key relationships is demanding. By properly utilizing the innovative ideas of these specialists, and applying leading edge technologies, true value is being generated for the share holders of the companies involved in the play. The discoveries of Mahogany and Teak have generated not only excitement in the Gulf Coast oil industry, but on Wall Street and in Washington as well. The possibility of another major frontier in the United States could revitalize the domestic oil industry. But this new play brings additional competition, which brings added challenges. Continued wise utilization of creative people's talents and new technologies will be necessary to reap the true rewards of this play. The Subsalt Play The salt province offshore Louisiana is part of the larger Gulf Coast Geosyncline that is dominated by salt tectonics, growth faults, and clastic dominated Tertiary sedimentation (Fig. 1). The province is known for its prolific production of hydrocarbons, and has remained one of the hottest drilling provinces in the world. The offshore Louisiana basin is also one of great geologic complexity with future treasures waiting to be discovered, as is proven by the recent discoveries in the subsalt play. Without this complexity, how else could such a heavily drilled province hold so much future potential? The basin contains massive quantities of Jurassic salt that has mobilized and formed complex structures. Until recently, most of the mobilization was believed to have been vertical, with the less dense plastic salt rising through sediment that was deposited above it. We now know that there is also a strong horizontal component to the salt movement, and that horizontal salt sheets cover over 30% of the offshore Louisiana shelf. The horizontal emplacement mechanism is what creates the subsalt play. In other basins world wide there have been presalt plays, where drilling through salt has encountered large reserves beneath the salt. The difference is that in the presalt play, the rocks beneath the salt are older.

Abstract This paper will investigate new techniques of using interactive three dimensional graphics design software to generate subsurface models. This application uses object-oriented software technology that was originally developed for solids modeling design, The graphic representation of all the objects is based on NURBS (Non-Uniform Rational B-splines) math which allows each graphic element to be represented by the same basic mathematical expression. Solid and surface models created using these software techniques provide the geoscientist the capability to use Boolean logic to find intersection and volumes of complex geologic structures. Introduction In today's exploration environment, It is essential for the geoscientist to utilize all available data to generate the most accurate model possible of the subsurface geology. The more accurate the model, the more informed the decision maker Is In choosing between costly alternatives. Advances In computer technology have allowed the user to create three-dimensional displays for visualization of the model. Visualization alone, albeit a very powerful tool, does not allow the model to be modified, manipulated and analyzed to its fullest. A new technique, which has proven successful in the automotive and aerospace Industries, can now also be applied to subsurface data to create a dynamic three-dimensional model. Traditional methods for gridding and contouring subsurface data to create a model are acceptable for many geologic structures which do not have a high degree of geometric complexity. However, when geologic and therefore geometric complexity Increase in areas such as salt domes or sand channels, the situation arises where there may be multiple z-values for a given x,y coordinate. In such cases it Is difficult for traditional methodology to describe an accurate model. When this occurs the geological structure has to be separated Into three parts or until each z value has Its own x,y. In addition, the Introduction of faults and/or boreholes (wells) increases the geometric complexity of the model. An approach which will allow the manipulation of the subsurface structure, as well as handle its geometric complexities, will allow the geoprofessIonal to more accurately define thesubsurface model. This paper proposes such an approach with examples which confirm Its validity for the cases studied. The techniques used by professionals In many other industries to accurately define and manipulate three dimensional models is based upon advances In solids modeling. Recently, three key advances in softwaretechnology allow these techniques to be applied. The first is the ability to work in a three-dimensional graphics domain. The second Is the approach used tomathematically define the geometry of the model. This approach takes advantage of math libraries based upon NURBS (Non-Uniform Rational B-Spllnes), and their ability to represent multiple geometric shapes. The third advance is in the area of object-oriented software, a programming technique used to describe real-world objects and their relationships with each other. Thecombination of three dimensional graphics, NURBS, andobject-oriented programming techniques provides a powerful tool to describe the geometry of virtually any solid body.