Geophysical Methods of Prospecting

Before prospecting is begun, all available information that would be of value should be collected and analysed. There may be several sources of information. Geologic maps and reports are very useful for this. Articles in technical journals may also deal with all or part of the district where the mineral deposit is found. The great value of geological information is not only to assist the location of mineral de­ posits but also to provide data for more accurate determi­nation of the horizons and extent.

In recent years there have been great achievements in different sciences, and in the light of growing knowledge the traditional part played by geologists in search for miner­als has been assisted by the application of geophysical methods of prospecting. By these methods the differences in the physical properties of subsoil and strata are measured with the aid of highly sensitive scientific instruments. The properties of electrical conductivity, magnetic permeability, density, elasticity and radioactivity are all used for this pur­pose. Equipment necessary for prospecting includes different tools, dynamite, compass and surveying instruments. More detailed prospecting will require more complete equipment including geophysical instruments and diamond drills.

So, geophysical methods of prospecting have become a useful means of searching for hidden mineral deposits. These methods are applied to locate mineral deposits or geo­ logical structures beneath the surface of the earth. Six basic geophysical methods: gravity, seismic, magnetic, electro­magnetic, electric and radiometric are usually used in the search for minerals.

Gravity methods depend upon the relative density of the ore deposit and surrounding wall rock, and are not much used in metalliferous exploration. This method has been suc­cessful in exploring for large deposits of petroleum, natural gas, sulphur, salt and coal.

Seismic methods have little use in metalliferous exploration because of the complicated geology of the typical ore deposits and because of the high cost of seismic work. These methods provide data for the determination of the depths and shape of reflected surfaces. Seismic prospecting is used in searching for oil, natural gas, coal and salt.

Magnetic Methods. Certain minerals distort the earth's magnetic field, and where large concentrations of such minerals occur, variations can be measured by mag­netometers. Magnetite iron ores have been found in many areas of the world using magnetometers.

Electromagnetic Methods. Of the various electrical methods of prospecting the electromagnetic (EM) systems have been applied with great success in exploration for mas­sive sulphide ores. Natural electrochemical reactions near the surface of the earth, where metallic sulphides may be subjected to weathering, can be used. The measuring in­strument detects the electrical current developed during the weathering of sulphides.

It should be noted that experiments involving the electro­magnetic sounding of the Earth's crust were first held in the USSR and other countries in the 1950s. But until recently geophysicists mainly took into consideration natural varia­tions in the Earth's magnetic field. Now scientists have instruments that can "see through the Earth" and with the help of them they can make experiments in electromagnetic sounding of vast territories at depths of dozens of kilometers.

Radiometric methods. Uranium, thorium, and potas­sium occur naturally in the earth materials and being radio­ active anomalies they may be detected by radiometric sur­veys. Radiometric surveys were successful in exploration for uranium.

The latest scientific achievements provide new meth­ods of prospecting. Thus, remote sensing involves the de­tection by sensors in spacecraft, rockets, or aircraft of the reflected or emitted radiation from the Earth's surface and subsequent analyses of these signals. It is already known that different surfaces with varying properties emit different amount of radiation. The study of these differences enables scientists to have more information on the natural resources of countries, especially of coal reserves. But this type of prospecting is not very productive as yet and in forms only a small part of total coal prospecting.

Timing has a great importance in multimodal interfaces since it can convey information and have effects on the interpretation process of statements. Figure 1 shows that the same interaction can be interpreted into two different ways depending on the precise temporal distribution of events and in particular on their temporal closeness. The following examples have been encountered in the MEDITOR application (a multimodal text editor). In the first example, the user points at a first character while saying, "begin selection". Then he points at another character while saying "end selection". The text between the two characters is then selected. Now, he says, "bold". This puts the selected text in bold. Finally, he points at another character and says, "delete". Only this last character is then deleted. In the second example, the third pointing operation is done just after saying, "bold". This temporal proximity allows the user to specify that the bold attribute must be applied only to the last character indicated and not to the current selection (which is still valid). Since the word "delete" is produced alone, it is applied to the current selection.

Finally, in the first example the selected text becomes bold and the third pointed character is deleted. In the second example we obtain the inverse result though the event sequences are exactly the same in both cases.

Let us consider another example which can be encountered in the context of a chemical factory. In the first example of fig. 2, the operator asks the system for the pressure value by pronouncing the word "pressure". The pressure value is then sent through the speech synthesiser. Then he decides to increase the temperature value by pointing at the temperature icon on his touch screen while saying "plus two". In the second example, the operator starts by pronouncing the sentence "pressure plus two".

Temporal Proximity. Temporal proximity between information may indicate a high probability of co-references, which means that data coming from different devices must be merged. It increases the power of the language by adding a new degree of freedom in the expression space. This notion is used since long time in graphical interfaces through the double-click. Double-click is significant only if the two clicks which compose it are close in time. In that case, these two clicks will not be interpreted separately but they will be merged to constitute a new event, which will lead to a new interpretation. However, temporal proximity is not easy to be exploited through a single modality. It is more interesting to exploit it with several modalities.

To solve this problem, it is first necessary to know the production instants of each word (beginning and end times), so it will be possible to retrieve the right chronological order of events. Then, an event must be handled only after ensuring that no other event is currently being produced by another device, because it is possible that the other event can have an earlier start time. So, we will ensure that the next event produced will have a later time production and we can be sure that events from all devices will be handled in the real chronological order. Concerning speech recognition systems, to check if an event is currently being produced means to check if the user is speaking or if the system is currently doing the recognition process. Unfortunately speech recognition systems do not always provide such information. The same problem is encountered with gesture recognition systems. In both cases it's important to know the user state (is he speaking? is he doing gestures?) and the recognition system state (acquisition, recognition...).

A long logistics supply chain exists in the flow of military cargo from installations in the continental United States to a theater of operations outside of the continental United States. Historically, simulation of this supply chain has involved various simulations to handle different components such as the individual nodes (military installations, seaports, airports) and the individual transportation legs (highway, rail, sea, air). To address the end-to-end nature of the problem, results from different simulations are used as input for other simulations. Alternatively, an effort to create a framework around the existing simulations to allow sharing of data has been conducted. The work presented here resulted from one of the simulations used in the end-to-end process, which identified the competition of transports shuttling cargo between cargo terminals as a critical resource.

An end-to-end simulation architecture is presented here that focuses on the availability of resources between and within cargo terminals. This architecture is not concerned with the transportation infrastructure between cargo terminals except as a delay factor. This architectural model was designed with the following

requirements:

• Operation of a network of cargo terminals: The architecture supports the operation of multiple cargo terminals connected in a network to enable the simulation of an end-to-end (origin to destination) cargo flow.

• Reconfigurable cargo terminals: An individual cargo terminal has the ability to be initialized independent of other cargo terminals. The cargo terminals are also reconfigurable; that is, the infrastructure and the resources in a cargo terminal as well as the sequence of cargo flow through the areas in a single terminal are changeable. This is important since the military regularly does not receive full access to a seaport as ongoing commercial shipping activities are

maintained.

• Concurrent deployment and redeployment: Previous efforts focused on the flow of cargo to the theater of operations (deployment). However, for sustainment, cargo will eventually be moving in a bidirectional manner. To support this, the architecture supports concurrent inbound and outbound flow of cargo within a single cargo terminal and bidirectional flow between terminals.

• Simulation of one million pieces of cargo: The architecture can support the simulation of the complete flow of one million pieces of cargo (with the cargo being modeled as individual pieces) within a reasonable execution time. While past analyses have studied individual cargo terminals and transportation network infrastructure, little effort has been made to study the complete end-to-end process at the cargo entity level, including detailed processing within the cargo terminals. This effort presents a complete model with a high level of fidelity in operational data and processes, while still maintaining high performance and scalability in problem size. The model develops a high-fidelity model for the cargo terminals modeling all internal resources (container handlers, stevedores, drivers, etc.) and infrastructure (cargo loading/offloading space, staging space, etc.). Internodal connections focus on modeling the impact of transportation resources (trucks, trains, ships, etc.) without worrying about the transportation infrastructure (roads, rail, waterways, etc.). The impact of transportation infrastructure is modeled in the form of time delays between nodes. This paper will present the network architecture supporting the simulation.

It will then illustrate how the architecture enables the simulation of a unique military scenario that includes new technology (as yet untested) in a scenario involving approximately one million pieces of cargo.