EP1228291A1

EP1228291A1 - Device and method for drilling in a subsurface

Info

Publication number: EP1228291A1
Application number: EP00980103A
Authority: EP
Inventors: Bastiaan Karel Jacques Obladen
Original assignee: Ballast Nedam Infra BV
Current assignee: Ballast Nedam Infra BV
Priority date: 1999-11-11
Filing date: 2000-11-03
Publication date: 2002-08-07
Also published as: NL1015324C2; AU1740301A; WO2001034941A1; AU773458B2

Abstract

The present invention relates to a method for drilling and/or pressing in a subsurface, comprising the steps of: predetermining the method of controlling drilling means for drilling and/or pressing in the subsurface; operating the drilling means in the predetermined manner; determining deformation data of the subsurface during the drilling and/or pressing; determining substantially in real-time the method of operating the drilling means subject to the deformation data.

Description

DEVICE AND METHOD FOR DRILLING IN A SUBSURFACE

The present invention relates to a method and a device for drilling in a subsurface, more particularly for drilling a tunnel in a ground.

Known for drilling tunnels or other engineering structures in a deformation- sensitive ground are recently developed tunnel boring machines, wherein ground material is excavated using a cutting wheel on the end of a steel tube, referred to as a shield, which ground material is transported above the ground surface using a liquid. The shield connects onto the already manufactured part of the tunnel wall, which is built up of successively placed rings, wherein one additional ring at a time is added to the tunnel wall per predetermined displacement of the shield. The progress of the shield with the cutting wheel placed therein is effected by thrusting the shield against the tunnel wall using a number of pressure jacks.

Such tunnel boring machines are controlled for the most part manually by a driver or operator trained for this purpose. The operator can control the drilling process using a number of control parameters, including the rotation speed of the drill, the degree of thrust of each of the pressure jacks, the discharge speed of the dislodged ground material and so on.

A drawback of such tunnel boring machines is that deformations may occur on the surface of the subsurface, i.e. displacements of the subsurface in both horizontal and vertical direction, which may cause serious damage to the infrastructure and the buildings on the surface. In order to minimize said deformations, the operator adjusts the control parameters of the drilling machine on the basis of his training and experience. The operator can also make use here of theoretically defined control parameters calculated using for instance a finite element model of the ground and the drilling machine on the basis of the measured deformations and ground parameters representative of the properties of the ground .

A drawback hereof is that calculation of such control parameters requires a long calculation time. A

; further drawback is that a large amount of data relating to the structure of the ground has to be available to calculate the control parameters, requiring an extensive system of measurements in the ground. This data will moreover have to be refreshed repeatedly since the

) structure of the ground is subject to changes along the route .

It is therefore an object of the present invention to provide a method and device for drilling in a subsurface, wherein the above stated drawbacks are

. obviated.

According to a first aspect of the present invention there is provided a method for drilling in a subsurface which comprises the steps of :

- predetermining the manner of controlling . drilling means for drilling and/or pressing in the subsurface ;

- operating the drilling means in the predetermined manner;

- determining deformation data of the subsurface 5 during drilling;

- determining substantially in real-time the manner of operating the drilling means subject to the deformation data. The method preferably further comprises of repeatedly determining the deformation data during o drilling, and in each case determining the optimal manner of operating the drilling means subject to the deformation data. Such a manner of operation is preferably parameterized in a number of control parameters. The starting point for drilling are then

5 predetermined control parameters with which the drilling can commence. During drilling the deformations on the surface of the subsurface are then measured, either directly by means of settlement beacons placed on the ground or indirectly by measuring displacements of buildings. It is noted that the manner of operating can not only be made dependent on the outcome of the deformation measurements, but also on the outcome of

; measurements of other status data, such as the pressure at a number of positions close to the drilling means, the pressure and flow rate in particular conduits or other elements of the tunnel boring machine . Making use of the deformation data, and optionally taking into account

) predetermined specific deformation limits, an optimal manner of operating the drilling means is determined which may or may not be modified. This determination of the manner of operating takes place substantially in real-time, so that more or less direct relationships can

5 be made between the control parameters on the one hand and the measured deformations and/or status data on the other .

A further advantage of the method according to the invention is that the manner of operating is o essentially independent of the structure of the ground and independent of the noise in the measurement data used. The changes of the ground in time or the distance covered are moreover included in the measurement data itself .

5 In a particular preferred embodiment the determining of control parameters on the basis of deformation data of the subsurface and the status data takes place using control parameter determining means, such as expert systems, which incorporate knowledge and o experience of the relations between deformation data and control parameters . Such expert systems can comprise a large number of "rules" or fixed relationships with which the correct control parameters are determined. In a particularly advantageous embodiment of the invention the

5 expert system comprises a neural network in which the relations between the deformation data, status data and control parameters can be determined. According to a preferred embodiment of the invention the method therefore comprises of :

-a) predetermining control parameters for controlling drilling means;

-b) operating drilling means with the predetermined control parameters for drilling and/or pressing in the subsurface;

-c) determining deformation data of the subsurface during drilling and/or pressing; j -d) determining status data during drilling and/or pressing;

-e) inputting the deformation data and the status data into control parameter determining means which, subject to the deformation data and status data,

_ determine the control parameters with which the drilling means can be operated, and continuing with step c) .

In accordance with the above stated preferred embodiment, step e of the method comprises of inputting the deformation data and status data into a neural o network and outputting the control parameters determined with the neural network. The output of the neural network provides the operator with a number of control parameters for controlling the drilling means. The operator may or may not make use hereof in controlling the tunnel boring s machine .

The steps of determining the deformation data and inputting deformation data into a neural network are preferably repeated so often that the neural network is trained on the basis of the status data, the inputted o deformation data and the control parameters ultimately chosen by the operator for controlling the drilling means. It is hereby possible for instance to transfer the knowledge and experience of the operator to the neural network.

5 According to another preferred embodiment the neural network is trained beforehand, for instance during drilling of an earlier tunnel or conduit, so that training of the neural network can be dispensed with during drilling of a subsequent tunnel or conduit.

According to another preferred embodiment of the invention the method comprises of showing an operator one or more of the determined control parameters . The operating person or the operator can then determine on the basis of the shown control parameters which control parameters he would like to use to operate the drilling means . According to another preferred embodiment the drilling means are directly operated with the control parameters calculated by the neural network, i.e. without direct intervention of the operator. Depending on the situation, a well-trained neural network can produce a better drilling performance than an operator.

According to a further preferred embodiment the method comprises of comparing the predetermined manner of operating (step a) with the manner of operating the drilling means determined in step e and, subject to the result of the comparison, choosing a preferred manner of operating the drilling means. The comparison comprises for instance of determining the difference between the control parameters. If the difference is greater than a predetermined value, the operator is for instance informed thereof by means of an acoustic or optical warning signal .

According to a further preferred embodiment the method comprises of repeating the steps a to e per predetermined drilling distance, which preferably corresponds with the length of the above mentioned rings of the tunnel wall . For each new ring the starting point is the predetermined starting value of the control parameters, which may or may not then be adjusted on the basis of the results of the calculations using the neural network.

According to a further preferred embodiment the method comprises of adding to the neural network analytically predetermined limit values for predicting unstable situations, whereby such situations can be avoided in improved manner.

According to a further preferred embodiment control parameters used during the drilling of a first tunnel or conduit are stored, for instance in a database, while during drilling of a second tunnel these control parameters are retrieved and compared with the control parameters determined for drilling the second tunnel or conduit . Use can hereby be made of the experience acquired in drilling the first tunnel, whereby the risk of deformations and the like can be further reduced.

According to a further preferred embodiment the step of determining deformation data comprises of measuring the deformations at positions in front of, above and behind the drill shield of the drilling means, and/or this step comprises of measuring deformations as a function of the elapsed time.

According to a further preferred embodiment of the invention, the method comprises of simulating the drilling of the tunnel or conduit in the subsurface on the basis of a physical model of inter alia the subsurface and of the drilling means. Rather than performing actual drilling, the drilling is simulated in this embodiment using the physical model . Such a simulation is preferably performed for the purpose of training an operator, who can hereby gain experience without any danger of damage occurring. Such simulations can moreover be performed in advance, i.e. before drilling, to enable the drilling to be optimized. According to a further embodiment the method comprises of testing one or more components of the drilling means by simulating the drilling. At least one component can hereby be tested in a factory or on-site without an expensive test drilling being required for this purpose.

According to a further embodiment the method comprises, for instance in the case of a calamity occurring, of stopping the drilling, simulating a number of drilling variants, choosing a drilling variant and continuing the drilling with the chosen drilling variant.

By simulating a number of possible drilling variants, the most optimal drilling variant can be chosen with which to continue the drilling. The adverse effects of the calamity are herein minimized.

According to another aspect of the present invention, there is provided a device for drilling in a subsurface, comprising - drilling means for drilling in a subsurface;

- control means connected to the drilling means for controlling the drilling means;

- deformation determining means for determining the deformation data which are a measure for the deformations caused by the drilling;

- status determining means for determining the status data which are characteristic of the drilling process;

- communication means for communicating between the deformation determining means, the status determining means and the control means; wherein the control means are equipped for determining substantially in real-time the manner of operating the drilling means.

According to a further preferred embodiment of the invention the drilling means comprise:

- a shield member with a rotatable drilling element arranged thereon;

- a number of pushing members between an outer end of the shield member lying opposite the drilling element and the tunnel wall for pushing along the shield member; wherein both the drilling element and the pushing members can be operated via the control means.

In a particular preferred embodiment the drilling itself takes place by rotating a drilling element, such as for instance a cutting wheel, which is controlled by control means, while displacing of the shield member takes place by means of a number of pushing members, such as pressure jacks and the like, which can likewise be operated using control means . In another preferred embodiment the drilling in the subsurface takes place by pressing an element, such as for instance a steel pipe, through the ground. Deformations on the surface of the subsurface may also occur in such a case. When therefore the term "drilling" is used in the following for making an opening in the subsurface, this is also understood to mean "pressing" or "arranging" elements in similar manner in a subsurface . The drilling means preferably also comprise spraying means for spraying filling material, which spraying means can be connected to the control means for control thereof . The operation and the purpose of the above-stated spraying means will be elucidated hereinbelow. The manner of drilling can be modified by operating the spraying means.

The drilling element, the pushing members and the spraying means can be operated by the control means, wherein the manner of operating hereof is determined by providing the correct control parameters thereto.

Further advantages, features and details of the present invention follow from the description hereinbelow of a preferred embodiment thereof. Reference is made in the description to the annexed figures, in which: - figure 1 shows a schematic view in perspective of a tunnel boring machine which is drilling a tunnel beneath two buildings;

- figure 2 shows an enlarged view of the preferred embodiment of figure 1, and - figure 3 shows a diagram giving a schematic explanation of the operation of the embodiment of fig. 1.

When a tunnel or similar structure is being constructed in a subsurface susceptible to deformation, such as for instance a relatively soft ground, at least two techniques are available. Firstly, a trench can be excavated in the subsurface, in which tunnel segments are arranged, whereafter the trench may or may not be covered again. Such a technique can be applied both on land and under water. The cost of constructing a tunnel in accordance with such a technique is relatively low. A drawback of this known technique is however that it cannot be applied, or only with great difficultly, in densely built-up areas. It is moreover hardly socially acceptable in particular cases to construct such tunnels in nature reserves, areas of particular cultural- historical nature or similar areas. A further drawback is that when such a tunnel is constructed in such a case the existing infrastructure of roads, and lines for water, electricity and communication etc. have to be adapted for a longer period, which may result in high indirect costs. In accordance with a second technique, the tunnel is drilled in a subsurface susceptible to deformation using a tunnel boring machine 1 (TBM) . Such a tunnel boring machine 1 is shown in figure 1. In the figure a tunnel is being dug in a ground B using tunnel boring machine 1. The already completed part of the tunnel wall consists of a number of successively placed concrete tunnel wall rings R. At the drilling end of the tunnel a steel tube or shield 6 is provided, this shield being shown in more detail in figure 2 and having dimensions which are slightly larger than those of the tunnel wall rings R, so that shield 6 is shifted some distance over the last tunnel wall rings of the tunnel wall (fig. 2) . A rotatable cutting wheel 2 is provided at the drilling end of shield 6. The cutting wheel 2 is set into rotation (to the left or the right) by an (electric) drive motor 3 arranged on shield 6. The cutting wheel 2 dislodges the ground material from the ground B as it rotates, wherein shield 6 is simultaneously pushed forward in a translating movement in the direction of arrow A. This pushing takes place by means of a number of pressure jacks 5 arranged between shield 6 and the last tunnel wall ring R. Pressure jacks 5 are herein distributed evenly over the end surface of tunnel wall ring R.

Each tunnel wall ring R is built up of a number of, for instance seven, segments S. When a tunnel wall ring R is mounted, said pressure jacks 5 must be retracted pairwise to leave space for the segment S for placing. A new tunnel wall ring R is arranged in each case against the last tunnel wall ring by successively arranging new tunnel wall segments S, whereby the length of the tunnel is increased in steps of one tunnel wall ring .

The ground material b dislodged during excavation is discharged as follows in the shown embodiment . Via a o liquid supply tube 12 bentonite liquid is supplied to a space between the cutting wheel 2 and a pressure bulkhead 14 placed therebehind of shield 6. The dislodged ground material b also ends up in this space. The bentonite liquid mixes with the dislodged ground material and the s mixture is discharged via a suction nozzle 13 and a discharge conduit (not shown) to a location above the ground surface.

In order to realize sufficient stability, an increased air pressure is necessary on the bentonite o liquid surface so as to be able to withstand the water and ground pressure at the relevant depth. For this purpose a second wall, the so-called safety wall 15, is placed in shield 6. By providing a compressed air cushion or compressed air bubble 17 between safety wall 15 and 5 pressure bulkhead 14, this pressure is transmitted via the bentonite liquid onto the drilling front.

In figure 2 the safety wall 15 has an opening on the underside so that the dislodged ground material can be drawn off via suction nozzle 13. In the case of o maintenance work however, safety wall 15 can be closed and maintenance staff can enter the space between pressure bulkhead 14 and safety wall 15 via air lock 16.

The tunnel boring machine 1 also comprises one or more displaceable trailers 7 on which a supply of tunnel 5 segments S are supported. Further arranged on trailers 7 are a number of pumps, for instance for supplying bentonite liquid respectively discharging the mixture of bentonite liquid and dislodged ground material via a number of feed and drain conduits.

Between the end of the shield 6 extending over the tunnel wall on the one hand and the tunnel wall on the other there is provided a tail seal 10, in which a feed mechanism 19 for feeding a grout mixture can be arranged. The feed mechanism serves to spray grout material into the space created around the tunnel wall during drilling, this because the outer diameter of shield 6 is larger than the outer diameter of the tunnel wall, and because in many cases the shield 6 is not positioned wholly parallel to the tunnel wall. This space is filled with grout material in order to prevent as far as possible subsidence on the surface of the ground B. The tunnel boring machine 1 can be operated with a number of adjustable control parameters, such as for instance the rotation speed and rotation direction of cutting wheel 2, the moment transmitted by cutting wheel drive 23 onto cutting wheel 2, the pressing force of each of the pressure jacks 5, the pressure of the bentonite supplied via the feed 12, the degree of suction via suction nozzle 13, the quantity and composition of the grout material sprayed around the tunnel wall via feed mechanism 19 and so on. During adjustment use can be made of status information obtained via a large number of sensors, such as pressure sensors 20 for measuring the pressure in the drilling area, sensors 21 for measuring the hydraulic pressure of each of the jacks 5 and/or the distance over which each of the jacks 5 is pushed out, flow rate meter 22 arranged in fed channel 19 for measuring the flow rate of the supplied ground material, etc .

On the surface of the ground B measurements are carried out on the displacements in upward and downward direction resulting from the approach and passage of tunnel boring machine 1. The settlement, when only vertical displacements are taken into account, or the deformations, when horizontal displacements are also taken into account, can be measured directly using settlement beacons 24, or indirectly using measuring equipment 25 arranged on a building G. The measurement data are received in a processing unit and transmitted s therefrom to tunnel boring machine 1. The measurement data can be displayed graphically. The measuring equipment is placed at a position in front of, above and behind the shield of the tunnel boring machine, in order to be able obtain a good picture of the deformations of o the ground surface caused by the drilling.

Prior to drilling the initial parameters for controlling the tunnel boring machine are determined on the basis of soil mechanical calculations. The drilling begins with the setting of these initial parameters. s During drilling the deformation data are sent substantially in real-time to the operator, this deformation data together with the status data being used to operate the tunnel boring machine with control parameters such that deformations (settlement) remain 0 minimal. The steps of determining the settlement data right up to operating the tunnel boring machine 1 take place during drilling and are therefore performed substantially in real-time, which means that the time delay is minimal. A time delay of a maximum of about half 5 an hour occurs in practice. A time delay of a maximum of 5 to 10 minutes can however be realized in some cases.

Shown schematically in figure 3 is the operation of the tunnel boring machine. Tunnel boring machine 1 is controlled using a TBM control 40. This control 40 is o connected using a large number of connecting lines 41a, 41b, .... , 41c, 41d to the various elements of tunnel boring machine 1 for controlling among other things the jack pressure, the rotation speed and rotation direction of cutting wheel 2 etc., as well as to status determining 5 sensors, such as sensors 20, 21, 22. In practice many hundreds or more sensors can be applied to determine any of the quantities which are representative for the drilling process. Pressure sensors at various positions, temperature sensors etc. can be envisaged here.

The control 40 of tunnel boring machine 1 is connected to a control computer 45 which can be operated

5 by an operator 0. Control of tunnel boring machine 1 takes place for instance by reducing the displacement speed of shield 6 (for instance by reducing the jack pressure in jacks 5) . Large deformations can hereby be avoided, since by spraying the grout material as stated o above on the outside of the tunnel wall the ground B can be stabilized to a sufficient extent. Such a low displacement speed will however make drilling uneconomic. However, if the displacement speed is increased the risk of deformations increases, which may cause damage to

5 buildings and infrastructure.

In order to determine the tunnel path the operator 0 is assisted in a manner known in the field by a laser (not shown) which is disposed in the tunnel and which indicates the ideal drilling path. Making use of o the laser the operator 0 obtains an indication via the control 40 and control computer 45 of the extent to which the actually drilled tunnel path deviates from the ideal path.

The operator 0 is assisted in controlling tunnel

5 boring machine 1 by the tunnel boring machine computer 45 which either indicates which preferred values the different control parameters should have, given the drilling path to be followed, in order to minimize deformations on the surface of the subsurface b, or o directly operates the control 40, in which latter case the operator O has only a monitoring function.

Determining of the preferred control parameters takes place by inputting into a neural network 46 the data from the settlement beacons 24 or the measuring

5 equipment 25, which measure the deformations. The status parameters which characterize the drilling process are also inputted into neural network 46. Once the neural network 46 has been trained, the output of this network will produce the preferred control parameters. The thus determined control parameters are subsequently made known to the operator 0 in random manner, for instance by means of a graphic display on the screen of control computer 45.

In the determining of preferred control parameters the control parameters defined by neural network 46 can be compared with control parameters stored in the theoretical database 50, which is filled before drilling with theoretically determined control parameters . These control parameters can be determined for instance by performing theoretical calculations on the basis of a physical model of the subsurface and of the tunnel boring machine. The preferred control parameters can moreover be compared with the control parameters from an "as-built" database 51, in which control parameters are stored during the drilling of a previous tunnel, for instance the first tunnel of twin tunnels, or a tunnel previously constructed in a similar ground. In the case of differences being too large between the control parameters in theoretical database 50 and/or the "as- built" database 51 on the one hand and the control parameters calculated by the neural network on the other a warning is generated, for instance in the form of an optical or acoustic signal. Operator O can hereby adjust the control parameters manually in order to prevent calamities .

In the case where the neural network has not yet been trained, the deformation data and the status data are used as input and the control parameters used or applied by an operator 0 are used as output to train the coefficients of the neural network. If after a period of time during drilling the neural network has been sufficiently trained, the tunnel boring machine computer 45 can in some cases take over control from operator O.

In a preferred embodiment of the invention it is assumed that for adaptive adjustment of a tunnel boring machine there is a relation between what is and can be measured on and in front of the tunnel boring machine and the subsequent deformation (for instance settlement) of the ground above the work operations . The most important candidates for this relation can be identified using diverse analytical assist means, whereafter guidelines can be drawn up such that the probable deformation of the ground is minimized. When, in the case the deformations measured on the surface of the ground are settlements, a number of candidates for settlement variables have for instance been identified on the basis of strong correlations between the variations in these variables and variations in the surface settlement directly above the tunnel boring machine, a computer program can be run which contains a feed-forward neural network, wherein the neural network learns the historic value of the control parameters and the associated value for the settlement variables. The network herein learns the relation between control parameters and settlement variables as these apply to the local ground conditions. On the basis of the relation learned, a prediction can then be made of the resulting settlement variables, given adjustments to the control parameters.

Suppose for instance that two pressure parameters on the drill shield measured with pressure sensors show as status data a strong correlation with the final settlement directly above the tunnel boring machine. Since these pressure parameters cannot be directly controlled, a relation must be found between the control parameters for manipulating (for instance pressure at the front, drilling speed and grout pressure) (x(l) , .... , x(n)) and the pressures at the two positions on the shield (y(l), y(2)). Such a relation is denoted with F((xl),...., x(n)) = (y(l) , y(2)). Given a historic data set, such as becomes available during drilling, the function F(x) can be learned in a feed-forward neural network with for instance adaptive error-back propagation as rule. The size of the network must be kept limited so as to arrive at a good generalization as well as to prevent "overfitting" of the training set.

By using a "time window" for the historic values and regularly retraining the neural network in this

; changing training set, the network can be implicitly adapted to a changing ground composition affecting the relation between settlement variables and control parameters (in other words, the function F (x) changes as a result of changes in the ground composition, and

_ through repeated retraining the network can adaptively learn this changing function) .

A sliding window of a historic training data set can be used for the prediction. For each measuring point at the drilling front five values are calculated, the

. average of the previous five measuring points, the average of measurements T 6-T_1„U, T11-T , T_16-T 2. O . and the average of T₀-T_2Q. Taken as the output value for learning is the value of a sensor on the shield. In the case of for instance eight input sensors, such as pressure o sensors at the drilling front, there are therefore 5 x 8 = 40 input nodes, and in this case one output node. A training set with 20 times the first data point is taken as starting point, the network is then trained and predicts the subsequent values . The measured new values s are added to the training set according to the first-in- first-out principle, whereafter the network is once again trained on the slightly modified training set in order to predict the following values.

On the basis of the learned function the network o can make a correct prediction, for a set of control variables, of the pressures to be expected on the shield ( (yl) and y(2)) . For a stable ground composition this prediction is also found to be reliable here for a longer time. This makes it possible to predict the results of

5 possible adjustments and thus realize a better monitoring of the control of the tunnel boring machine .

Shown in figure 3 with a broken line is that the control parameters applied during drilling and the associated values of the status data for later use in a database, for instance the as-built database 51, can be stored.

In addition to the above described application of the invention to the drilling of tunnels in a subsurface, it will be apparent that the invention also includes other applications, such as application in the pressing of pipes into a subsurface, such as for instance pressing steel pipes through a soft ground in order to realize an oil pipeline etc.

In a further preferred embodiment of the invention the system of the tunnel boring machine computer 45, the neural network 46, the settlement measuring sensors 24 and 25 and optionally the databases 50 and 51 can be connected to a simulator 44 in which the behaviour of tunnel boring machine 1 is simulated. Such a simulator can be implemented in terms of both software and hardware .

Since connection of simulator 44 is optional,

) this is shown in figure 3 with broken lines. The simulator can however also function separately of the tunnel boring machine, for instance in order to simulate the drilling process before going ahead with the actual drilling, this being set forth hereinbelow.

_ In a simple simulation model behaviour is for instance simulated of the shield 6, pressure bulkheads 14,15, pressure jacks 5, cutting wheel 2 with displacement cylinders, a system for absorbing pressure variations, i.e. the system for the compressed air

_ cushion, the behaviour of the feed and discharge system for liquid and dislodged ground material, of compressors and air pressure control, the consequence of a particular water pressure, ground pressure, friction along shield 6, soil type and so on.

5 Using the simulator simulations can be carried out in advance for the drilling path which will be followed, with the object of optimizing the drilling path. Such a simulator can also be applied to train drivers or operators. Since in practice the training of operators takes a very long time (a number of years) , and hazardous situations moreover cannot be trained, or hardly so, it is more advantageous to train an operator on such a simulator. The simulator can also be applied when calamities occur. Here for instance drilling of the tunnel is halted, a simulation is carried out of the performed drilling work and an assessment is made of the situation to which the TBM must return to once again obtain a stable situation.

In another preferred embodiment the simulator can be used to enable testing of subsystems of the tunnel boring machine on the premises of the manufacturer of the tunnel boring machine (TBM) to see whether all subsystems are functioning correctly. In such a case the simulation of particular subsystems can be replaced during the manufacturing process by the actual subsystems or components at the moment these are ready. Once the whole machine is completed, the simulator can be connected to all subsystems of the tunnel boring machine and a trial run can take place. The test drilling usual in current practice (over more than 200 m) can hereby be avoided.

The present invention is not limited to the above described preferred embodiments thereof; the rights sought are defined by the following claims, within the scope of which many modifications can be envisaged.

Claims

1. Method for drilling and/or pressing in a subsurface, comprising the steps of:

- predetermining the manner of controlling drilling means for drilling and/or pressing in the

5 subsurface;

- operating the drilling means in the predetermined manner;

- determining deformation data of the subsurface during the drilling and/or pressing; o - determining substantially in real-time the manner of operating the drilling means subject to the deformation data.

2. Method as claimed in claim 1, comprising of repeatedly determining the deformation data during s drilling and/or pressing, and in each case determining the optimal manner of operating the drilling means subject to the deformation data.

3. Method as claimed in claim 1 or 2 , wherein the method of operation is determined by a number of control 0 parameters .

4. Method for drilling and/or pressing in a subsurface, preferably as claimed in claim 3, comprising the steps of :

-a) predetermining control parameters for 5 controlling drilling means for drilling and/or pressing in the subsurface;

-b) operating drilling means with the predetermined control parameters for drilling and/or pressing in the subsurface; o -c) determining deformation data of the subsurface during drilling and/or pressing;

-d) determining status data during drilling and/or pressing;

-e) inputting the deformation data and the status 5 data into control parameter determining means which, subject to the deformation data and status data, determine the control parameters with which the drilling means can be operated, and continuing with step c.

5. Method as claimed in claim 4, wherein step e comprises of inputting the deformation data and status data into a neural network and outputting the control parameters determined with the neural network.

6. Method as claimed in claim 5, comprising of training the neural network during drilling and/or pressing on the basis of the input of the determined deformation data and the status data and the output of the control parameters.

7. Method as claimed in claim 5 or 6 , comprising of training the neural network in advance .

8. Method as claimed in any of the claims 5-7, comprising step e of:

-el) showing an operating person one or more of the determined control parameters.

9. Method as claimed in claim 8, comprising step e of :

-e2) the operating person optionally adjusting the control parameters on the basis of the shown control parameters and operating the drilling means with the optionally adjusted control parameters.

10. Method as claimed in any of the claims 5-8, comprising step e of :

-e3) operating the drilling means with the determined control parameters .

11. Method as claimed in any of the claims 5-10, comprising of :

- comparing the manners of operating the drilling means determined in step a and in step e ; and,

- adjusting the manner in which the drilling means are operated subject to the result of the comparison.

12. Method as claimed in any of the claims 5-11, comprising of repeating the steps a to e per predetermined drilling distance.

13. Method as claimed in any of the foregoing claims, wherein the drilling comprises of excavating a tunnel or pressing a conduit into the subsurface.

14. Method as claimed in claim 12, wherein the predetermined drilling distance substantially corresponds with the length of an annular tunnel segment of the tunnel wall .

15. Method as claimed in any of the foregoing claims, comprising of adding to the neural network analytically predetermined limit values.

16. Method as claimed in claim 13, comprising of storing the control parameters and/or status data used during the drilling of a first tunnel or conduit.

17. Method as claimed in claim 16, comprising of comparing control parameters to be applied during drilling of a second tunnel or conduit with the control parameters applied during drilling of the first tunnel or conduit .

18. Method as claimed in claim 17, comprising of adjusting the control parameters to be applied subject to the comparison of the control parameters.

19. Method as claimed in claim 17 or 18, comprising of situating the first and second tunnel or conduit in the vicinity of each other.

20. Method as claimed in any of the foregoing claims, wherein the step of determining deformation data comprises of measuring deformations at positions in front of, above and behind the drill shield of the drilling means .

21. Method as claimed in any of the foregoing claims, wherein the step of determining deformation data comprises of measuring deformations as a function of the elapsed time.

22. Method as claimed in any of the claims 5-21, comprising in step a the use of soil mechanical and/or empirical relations to determine the predefined control parameters .

23. Method as claimed in any of the foregoing claims, comprising of simulating the drilling of a tunnel or conduit in the subsurface on the basis of a physical model of inter alia the subsurface and of the drilling

5 means .

24. Method as claimed in claim 23, comprising of training an operator by simulating the drilling of a tunnel in the subsurface.

25. Method as claimed in claim 23, comprising of o performing simulations in advance in order to optimize the drilling.

26. Method as claimed in claim 23, comprising of testing one or more components of the drilling means by simulating the drilling. s

27. Method as claimed in claim 23, comprising of stopping the drilling, simulating a number of drilling variants, choosing a drilling variant and continuing the drilling with the chosen drilling variant.

28. Device for drilling and/or pressing in a o subsurface, comprising

- means for drilling and/or pressing in a subsurface ;

- control means connected to the drilling and/or pressing means for controlling the drilling and/or 5 pressing means;

- deformation determining means for determining the deformation data which are a measure for the deformations caused by the drilling and/or pressing;

- status determining means for determining the o status data which are characteristic of the drilling and/or pressing process;

- communication means for communicating between the deformation determining means, the status determining means and the control means; wherein the control means 5 are equipped for determining substantially in real-time the manner of operating the drilling and/or pressing means .

29. Device as claimed in claim 26, wherein the control means comprise control parameter determining means for determining, subject to the deformation data and the status data, the optimal control parameters with

5 which the drilling and/or pressing means can be controlled.

30. Device as claimed in claim 29, wherein the control parameter determining means comprise a neural network which, with the deformation data and status data ιo as input, determines the optimal control parameters with which the drilling and/or pressing means can be controlled.

31. Device as claimed in claim 29 or 30, wherein the means comprise: i5 - a shield member with a rotatable drilling element arranged thereon;

- a number of pushing members between an outer end of the shield member lying opposite the drilling element and the tunnel wall for pushing along the shield 20 member; wherein both the drilling element and the pushing members can be operated via the control means .

32. Device as claimed in claim 29, 30 or 31, comprising spraying means for spraying grout material, which spraying means can be connected to the control

25 means for operating thereof.

33. Device as claimed in any of the claims 29-32, which comprises data storage means in which can be stored control parameters applied for drilling and/or pressing.

34. Device for drilling and/or pressing in a

30 subsurface, wherein the method as claimed in at least one of the claims 1-27 is applied.

35. Method for drilling in a subsurface, wherein the device as claimed in any of the claims 28-34 is applied .