The subject matter of the present invention relates to computer modeling of a gas reservoir, and, more particularly, to a method and apparatus and program storage device adapted for generating a computer model which will predict the pressure and the production behavior of a gas reservoir.
Reservoir simulation is an essential tool for the management of oil and gas reservoirs. Prediction of the pressure in and the production of a gas reservoir under various operating conditions allows, among other benefits, proper investment decisions to be made. In order to make such a prediction, one must construct a reservoir model. The reservoir model is essentially a mathematical model that is implemented through a computer program. History matching observed behavior of the reservoir must validate the parameters of the model. Ideally, finite difference simulators are used to construct reservoir models. This permits detailed characterization including heterogeneity, multiphase effects like water coning and fingering. However, in order to make full use of such a tool, a large amount of reliable data is required. Also, a full study, including the history matching step, may take months to carry out. Therefore, there is a demand for an alternative tool that honors the physics of fluid flow and, at the same time, generates a solution which is many orders quicker and faster than the aforementioned finite difference simulator.
One aspect of the present invention involves a method of generating a prediction of values in a reservoir, comprising the steps of: (a) receiving input data characterizing the reservoir; (b) producing a computer model in response to the input data representing the reservoir, the producing step (b) of producing the computer model including the steps of, (b1) calculating the values in one dimension associated with a single layer in the reservoir, each of the values existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b2) calculating the values in the one dimension associated with multiple layers in the reservoir, each of the values in each of the multiple layers existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b3) calculating the values in three dimensions associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b4) calculating the values in the three dimensions as a function of time, the values being associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir, the each of the values in the each of the multiple layers in the three dimensions existing at any future point in time in the reservoir, the computer model being produced in response to the calculating step (b4); verifying the computer model; and using the computer model, generating the prediction of the values in the reservoir in response to the verifying step.
Another aspect of the present invention involves a program storage device readable by a machine tangibly embodying a set of instructions executable by the machine to perform method steps for generating a prediction of values in a reservoir, the method steps comprising: (a) receiving input data characterizing the reservoir; (b) producing a computer model in response to the input data representing the reservoir, the producing step (b) of producing the computer model including the steps of, (b1) calculating the values in one dimension associated with a single layer in the reservoir, each of the values existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b2) calculating the values in the one dimension associated with multiple layers in the reservoir, each of the values in each of the multiple layers existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b3) calculating the values in three dimensions associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b4) calculating the values in the three dimensions as a function of time, the values being associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir, the each of the values in the each of the multiple layers in the three dimensions existing at any future point in time in the reservoir, the computer model being produced in response to the calculating step (b4); verifying the computer model; and using the computer model, generating the prediction of the values in the reservoir in response to the verifying step.
Another aspect of the present invention involves a system adapted for generating a prediction of values in a reservoir, comprising: first apparatus adapted for receiving input data characterizing the reservoir; second apparatus adapted for producing a computer model in response to the input data representing the reservoir, the second apparatus adapted for producing the computer model including, third apparatus adapted for calculating the values in one dimension associated with a single layer in the reservoir, each of the values existing at a single point in space in the reservoir and at a single point in time in the reservoir, fourth apparatus adapted for calculating the values in the one dimension associated with multiple layers in the reservoir, each of the values in each of the multiple layers existing at a single point in space in the reservoir and at a single point in time in the reservoir, fifth apparatus adapted for calculating the values in three dimensions associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir and at a single point in time in the reservoir, sixth apparatus adapted for calculating the values in the three dimensions as a function of time, the values being associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir, the each of the values in the each of the multiple layers in the three dimensions existing at any future point in time in the reservoir, the computer model being produced in response to the calculating performed by the sixth apparatus; seventh apparatus adapted for verifying the computer model thereby generating a verified computer model; and eighth apparatus, responsive to the verified computer model, adapted for generating the prediction of the values in the reservoir in response to the verifying performed by the seventh apparatus.
Another aspect of the present invention involves a method of producing a computer model in response to input data representing a reservoir, comprising the steps of: (a) calculating values in one dimension associated with a single layer in the reservoir, each of the values existing at a single point in space in the reservoir and at a single point in time in the reservoir, (b) calculating the values in the one dimension associated with multiple layers in the reservoir, each of the values in each of the multiple layers existing at a single point in space in the reservoir and at a single point in time in the reservoir, (c) calculating the values in three dimensions associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir and at a single point in time in the reservoir, and (d) calculating the values in the three dimensions as a function of time, the values being associated with the multiple layers in the reservoir, each of the values in each of the multiple layers in the three dimensions existing at a single point in space in the reservoir, the each of the values in the each of the multiple layers in the three dimensions existing at any future point in time in the reservoir, the computer model being produced in response to the calculating step (d).
Another aspect of the present invention involves a program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform method steps for producing a computer model in response to input data representing a reservoir, said method steps comprising: (a) calculating values in one dimension associated with a single layer in said reservoir, each of said values existing at a single point in space in said reservoir and at a single point in time in said reservoir, (b) calculating said values in said one dimension associated with multiple layers in said reservoir, each of said values in each of said multiple layers existing at a single point in space in said reservoir and at a single point in time in said reservoir, (e) calculating said values in three dimensions associated with said multiple layers in said reservoir, each of said values in each of said multiple layers in said three dimensions existing at a single point in space in said reservoir and at a single point in time in said reservoir, and (d) calculating said values in said three dimensions as a function of time, said values being associated with said multiple layers in said reservoir, each of said values in each of said multiple layers in said three dimensions existing at a single point in space in said reservoir, said each of said values in said each of said multiple layers in said three dimensions existing at any future point in time in said reservoir, said computer model being produced in response to the calculating step (d).
Another aspect of the present invention involves a system adapted for producing a computer model in response to input data representing a reservoir, comprising: first apparatus adapted for calculating values in one dimension associated with a single layer in said reservoir, each of said values existing at a single point in space in said reservoir and at a single point in time in said reservoir, second apparatus adapted for calculating said values in said one dimension associated with multiple layers in said reservoir, each of said values in each of said multiple layers existing at a single point in space in said reservoir and at a single point in time in said reservoir, third apparatus adapted for calculating said values in three dimensions associated with said multiple layers in said reservoir, each of said values in each of said multiple layers in said three dimensions existing at a single point in space in said reservoir and at a single point in time in said reservoir, and fourth apparatus adapted for calculating said values in said three dimensions as a function of time, said values being associated with said multiple layers in said reservoir, each of said values in each of said multiple layers in said three dimensions existing at a single point in space in said reservoir, said each of said values in said each of said multiple layers in said three dimensions existing at any future point in time in said reservoir, said computer model being produced when said fourth apparatus calculates said values in said three dimensions as a function of time.
A full understanding of the present invention will be obtained from the detailed description of the preferred embodiment presented hereinbelow, and the accompanying drawings, which are given by way of illustration only and are not intended to be limitative of the present invention, and wherein:
Prediction of the pressure-production behavior of a hydrocarbon reservoir is essential for its effective management. Project planning and screening functions depend on time availability of such information. There is a need for a fast solution that involves history matching and subsequent prediction. A Gas Reservoir Evaluation and Assessment Tool (GREAT) disclosed in this specification is based around a newly formulated set of equations applicable to multiple wells in a single-phase system. The GREAT tool provides a complete workflow for gas reservoir evaluation comprised of data entry and manipulation, model initialization, test interpretation, history matching and prediction. The GREAT tool includes the Analytical Engine 20 which further includes a newly derived solution of diffusivity equations for multiple wells, horizontal or vertical, in a single phase layered system under a variety of boundary conditions. The solution of these equations model both transient and steady state flow regimes and is applicable to both testing and long term performance prediction. The equations applicable to laminar flow of fluids in a porous medium were the results of Darcy's experimental study of the flow characteristics of sand filters. This combined with the equation of continuity and an equation of state for slightly compressible fluid yields the diffusivity equation, which is the equation for pressure diffusion in a porous medium Solution of the diffusivity equation under different boundary conditions forms the basis for a prediction of the bottom hole pressure response of a producing well. These analytical solutions are generally applicable for a single well and are used widely in the area of well testing. The efficiency of analytical models is generally judged by accuracy and speed. The novel set of solutions used in the GREAT tool is applicable to multiple wells, which can be vertical as well as horizontal. These wells can be operating as producers or injectors thus being of additional significance to gas well storage. The solution of the diffusivity equation set forth in this specification has been derived by application of successive integral transforms. The application of these new solutions is characterized by stability and speed.
Accordingly, in this specification, a Gas Reservoir Evaluation and Assessment Tool (GREAT) in accordance with the present invention utilizes an Analytical Engine (instead of a Finite Difference Engine) to produce predictions of pressure values and other production data at ‘any point in space’ and at ‘any point in time’ in a reservoir. A computer system, such as a workstation, stores a Gas Reservoir Evaluation and Assessment software which includes the Analytical Engine and responds to input data (which includes a reservoir description and fluid properties) by generating an output record which represents a prediction of the pressure values and other data at ‘any point in space’ and at ‘any point in time’ in a reservoir. The Analytical Engine will first calculate a pressure value in 1D for a single layer of a reservoir at a ‘single point in space’ and a ‘single point in time’; it will then calculate a pressure value in 1D for multiple layers in the reservoir at the ‘single point in space’ and the ‘single point in time’; it will then calculate a pressure value in 2D for the multiple layers at the ‘single point in space’ and the ‘single point in time’; it will then calculate a pressure value in 3D for the multiple layers at the ‘single point in space’ and the ‘single point in time’; and it will then calculate a pressure value in 3D for multiple layers not only at a ‘single point in space’ but also at ‘any future point in time’.
Referring to
Referring to
In
The Model Initialization step 12a will allow for initiation of the gas reservoir model with a basic model shape, layer geometry, and static properties, such as porosity. A range of correlation suites will be provided to generate fluid properties.
During the Test Interpretation step 14a, initial estimates of permeability and skin, D-factor, open flow potential, initial reservoir pressure, and reservoir volume can be made. Basic line fitting functionality on specialized transient pressure plots will be used for this purpose. Additionally, two basic material balance plots, i.e., Havlena—Odeh and p/Z, will be available to determine the reservoir volume from static pressure data.
The History Matching step 14b is essentially for model validation. Having obtained the initial parameter estimates from previous steps, non-linear regression can now be performed on the observed pressure data for all the wells in the reservoir. This would provide both final tuning of the reservoir and well parameters in the context of the entire reservoir.
The Prediction step 16 and 18 will use the tuned model to provide forecast of reservoir and well bottom hole pressures based on individual well targets. Individual well targets can be set from Daily Contracted Quantity (DCQ) and monthly profile factors. Individual well and reservoir pressure cutoffs along with swing factor will provide the necessary checks for determining the ability of a well to produce. This step will also provide an option to generate a numerical model of the reservoir for simulation engineers.
It should be noted that it is not essential to follow all the steps. If pressure transient data is not available, initial permeability values can be obtained from logs and reservoir volume can be obtained from geological information. One can move from the Model Initialization step to the History Matching step. Similarly, if no historical data is present, one may use the Prediction step as a design exercise.
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
In
In
In
In
In
In
In
40/42/44 for each formation layer 36a, 36b, and 36c (at the ‘single point in space’ and the ‘single point in time’) as shown in
In
In
In
The pressures values 30-52 were calculated (in ‘3D’ and as a function of ‘time’) by a successive integration of a Point Source Solution in the Diffusivity Equation where the flow rate is governed by Darcy's Law. The Gas Reservoir Evaluation and Assessment Tool (GREAT) of the present invention, as shown in
Referring to
A functional description of the operation of the Gas Reservoir Evaluation and Assessment Tool (GREAT) 22 of the present invention shown in
In
Referring to
In
The ‘Detailed Description of the Invention’ portion of this specification, set forth below, provides a ‘detailed specification document’ which discloses the construction of the Analytical Engine 20 of
Mathematical Operations of Special Functions
where
with initial condition p(x,y,z,0)=0, for x>0, y>0, z>0 and boundary conditions p(∞,y,z,t)=p(∞,y,z,t)=0, p(x,0,z,t)=p(x,∞,z,t)=0, p(x,y,0,t)=p(x,y,∞,t)=0, t>0.
We apply the Laplace transformation to equation (6.1.1). We get,
where
We now apply the appropriate Fourier transformations to equation (10.1.2). We get,
where
Successive inverse Fourier transforms of equation (10.1.3) yields
Inverse Laplace transform of equation (10.1.4) yields
where
is the Heaviside's Unit step function. As t→t0, pressure from equation (10.1.5) tends to zero at all points except at [x0, y0, z0] where it becomes infinite.
With a change of notation the equivalent solutions for heat and mass diffusion problems may be formally written as*
where the Q is the total quantity of heat instantaneously liberated at time t=t0 at a point [x0, y0, z0].
Mass Diffusion:
Here Q represents the amount of substance deposited at time t=t0 at a point [x0,y0,z0].
The continuous constant source solution may be obtained by integrating the instantaneous line source solution with respect to time. However, for illustrative purposes, here we solve the problem in a formal way. Fluid is produced at the rate of q(t) per unit time from t=t0 to t=t at the point [x0,y0,z0]. We find p from the partial differential equation
with initial condition p(x,y,z,0)=0, for x>0, y>0, z>0 and boundary conditions p(0,y,z,t) p(∞,y,z,t)=0, p(x,0,z,t)=p(x,∞,z,t)=0, p(x,y,0,t)=p(x,y,∞,t)=0, t>0. Following the procedure outlined earlier, the successive application of Laplace and Fourier transforms reduces equation (10.1.10) to an algebraic equation, which is
Successive inverse Fourier and Laplace transforms yield
and
If q(t) is a constant and equal to q, integration of equation (10.1.13) gives
For the case where q(t)=qtv, v≧0, t>0, integration or equation (10.1.13) gives
The solution corresponding to the case where instantaneous and continuous multiple point sources at [x0ι,y0ι,z0ι] at times t=t0ι, ι=1, 2, . . . , N, may be obtained by solving the partial differential equations
and
respectively. The solutions for instantaneous multiple point sources in an Octant are
and
The solutions for continuous multiple point sources are
and
We consider some special cases of practical relevance.
(i) A line of finite length [z02−z01] passing through (x0,y0).
The solution is obtained by simple integration. For an instantaneous source, we get
and
Solution for a continuous source is*
and
The spatial average pressure response of the line [z02−z01] is obtained by a further integration†.
and
(ii) Multiple lines of finite lengths [z02ι−z01ι], [x02ι−x01ι] and [y02ι−y01ι] passing through (x0ι,y0ι) for ι=1, 2 . . . , L, (y0ι,z0ι) for ι=L+1, 2 . . . , M, and (x0ι,z0ι) for ι=M+1, 2 . . . , N respectively. Where (L<M<N)*.
and
The spatial average pressure response of the line [z02⋄−z01⋄], ι=⋄, is obtained by a further integration.
and
The solution of equation (10.1.2) in the infinite region [−∞<x<∞], [−∞<y<∞] and [−∞<z<∞] may be obtained by taking the complex Fourier transform [equation (2.2.1)].
Successive inverse Fourier* and Laplace transforms of equation (10.1.14) are
and
respectively*. The corresponding continuous solution is given by
and
We consider some special cases of practical relevance.
(i) q(t) is a constant and equal to q
and
(ii) q(t)=qtv, v>0, t>0
and
(iii) A line of finite length [z02−z01] passing through (x0,y0). Instantaneous source
for a continuous source
and
For the case q(t) is a constant and equal to q
and
(iv) Spatial average pressure response of the line [z02−z01]
and
(v) Multiple lines of finite lengths [z02ι−z01ι], [x02ι−x01ι] and [y02ι−y01ι] passing through (x0ι,y0ι) for ι=1, 2 . . . , L, (y0ι,z0ι) for ι=L+1, 2 . . . , M, and (x0ι,z0ι) for ι=M+1, 2 . . . , N respectively. Where (L<M<N).
and
The spatial average pressure response of the line [z02⋄−z01⋄], ι=⋄, is obtained by a further integration.
and
and
We consider some special cases.
(i) ψyz(y,z,t)=ψyz(t), ψxz(x,z,t)=ψxz(t), ψxy(x,y,t)=ψzy(t), q(t)=0 and φ(u,v,w)=0,
and
(ii) ψyz(y,z,t)=pyx, ψxz(x,z,t)=pxz, ψxy(x,y,t)=pxy; pyx, pxz and pxy are constants. q(t)=0 and
and
(ii)
x>0, y>0, q(t)=0 and ψyz(y,z,t)=ψzy(x,y,t)=0
(iv)
x>0, y>0, z>0, q(t)=0 and ψyz(y,z,t)=ψxz(x,z,t)=ψzy(x,y,t)=0.
and
(v) A line of finite length [z02−z01] passing through (x0, y0).
and
The spatial average pressure response of the line [z02−z01] is obtained by a further integration
and
(vi) Multiple lines of finite lengths [z02ι−z01ι], [(x02ι−x01ι] and [y02ι−y01ι] passing through (x0ι, y0ι) for ι=1, 2 . . . , L, (y0ι,z0ι) for ι=L+1, 2 . . . , M, and (x0ι,z0ι) for ι=M+1, 2 . . . , N respectively. Where (L<M<N).
and
The spatial average pressure response of the line [z02⋄−z01⋄], ι=⋄, is obtained by a further integration.
and
and
We consider some special cases.
(i) A line of finite length [z02−z01] passing through (x0,y0).
and
The spatial average pressure response of the line [z02−z01] is obtained by a further integration.
and
(ii) Multiple lines of finite lengths [z02ι−z01ι], [x02ι−x01ι], and [y02ι−y01ι] passing through (x0ι,y0ι) for ι=1, 2 . . . , L (y0ι,z0ι) for ι=L+1, 2 . . . , M, and (x0ι,z0ι) for ι=M+1, 2 . . . , N respectively. Where (L<M<N).
and
The spatial average pressure response of the line [z02⋄−z01⋄], ι=⋄, is obtained by a further integration.
and
x>0, y>0. The initial pressure p(x,y,z,0)=φ(x,y,z). φ(x,y,z) and its derivative tend to zero as x→∞, y→∞ and z→∞.
The solution for the continuous point source is
and
We consider some special cases.
(i) ψyz(y,z,t)=ψyz(t), ψxz(x,z,t)=ψxz(t), ψxy(x,y,t)=ψxy(t), q(t)=0 and φ(u,v,w)=0.
and
(ii) ψyz(y,z,t)=pyz, ψxz(x,z,t)=pxz, ψxy(x,y,t)=qxy; pyr, pxz and qxy are constants. q(t)=0 and φ(u,v,w)=0.
and
(iii)
x>0, y>0, z>0, q(t)=0 and ψyz(y,z,t)=ψxz(x,z,t)=ψzy(x,y,t)=0.
and
(iv) A line of finite length [z02−z01] passing through (x0,y0).
and
The spatial average pressure response of the line [z02−z01] is obtained by a further integration.
and
(v) A line of finite length [x02−x01] passing through (y0,z0).
and
The spatial average pressure response or the line [x02−x01] is obtained by a further integration.
and
(vi) Multiple lines of finite lengths [z02ι−z01ι], [x02ι−x01ι] and [y02ι−y01ι] passing through (x0ι,y0ι) for ι=1, 2 . . . , L, (y0ι,z0ι) for ι=L+1, 2 . . . , M, and (x0ι,z0ι) for ι=M+1, 2 . . . , N respectively. Where (L<M<N).
and
The spatial average pressure response of the line [z02⋄−z01⋄], ι=⋄, is given by
and
The spatial average pressure response of the line [x02⋄−x01⋄], ι=⋄, is given by
and
and
(i) A line of finite length [z02−z01] passing through (x0,y0).
and
The spatial average pressure response of the line [z02−z01] is obtained by a further integration.
and
(ii) A line of finite length [x02−x01] passing through (y0,z0).
and
The spatial average pressure response of the line [x02−x01] is obtained by a further integration.
and
(iii) Multiple lines of finite lengths [z02ι−z01ι], [x02ι−x01ι] and [y02ι−y01ι] passing through (x0ι,y0ι) for ι=1, 2 . . . , L, (y0ι,z0ι) for ι=L+1, 2 . . . , M, and (x0ι,z0ι) for ι=M+1, 2 . . . , N respectively. Where (L<M<N).
and
The spatial average pressure response of the line [z02⋄−z01⋄], ι=⋄, is given by
and
The spatial average pressure response of the line [x02⋄−x01⋄], ι=⋄, is given by
and
x>0, y>0. The initial pressure p(x,y,z,0)=φ(x,y,z). φ(x,y,z) and its derivative tend to zero as x→∞, y→∞ and z→∞.
The invention being thus described, it will be obvious that the same may be varied in many ways. Such variations are not to be regarded as a departure from the spirit and scope of the invention, and all such modifications as would be obvious to one skilled in the art are intended to be included within the scope of the following claims.
This application is a continuation of prior application Ser. No. 11/227,540, filed Sep. 15, 2005.
Number | Name | Date | Kind |
---|---|---|---|
2727682 | Patterson | Dec 1955 | A |
3373805 | Boberg et al. | Mar 1968 | A |
4518039 | Graham et al. | May 1985 | A |
4828028 | Soliman | May 1989 | A |
5414674 | Lichman | May 1995 | A |
5501273 | Puri | Mar 1996 | A |
5787050 | Slevinsky et al. | Jul 1998 | A |
5960369 | Samaroo | Sep 1999 | A |
5992519 | Ramakrishnan et al. | Nov 1999 | A |
6002985 | Stephenson | Dec 1999 | A |
6018497 | Gunasekera | Jan 2000 | A |
6041017 | Goldsberry | Mar 2000 | A |
6052520 | Watts, III | Apr 2000 | A |
6078869 | Gunasekera | Jun 2000 | A |
6106561 | Farmer | Aug 2000 | A |
6128580 | Thomsen | Oct 2000 | A |
6131071 | Partyka et al. | Oct 2000 | A |
6135966 | Ko | Oct 2000 | A |
6230101 | Wallis | May 2001 | B1 |
6263284 | Crider et al. | Jul 2001 | B1 |
6313837 | Assa et al. | Nov 2001 | B1 |
6356844 | Thomas et al. | Mar 2002 | B2 |
6374185 | Taner et al. | Apr 2002 | B1 |
6498989 | Pisetski et al. | Dec 2002 | B1 |
6502037 | Jorgensen et al. | Dec 2002 | B1 |
6591201 | Hyde | Jul 2003 | B1 |
6724687 | Stephenson et al. | Apr 2004 | B1 |
6799117 | Proett et al. | Sep 2004 | B1 |
6842700 | Poe | Jan 2005 | B2 |
6901391 | Storm, Jr. et al. | May 2005 | B2 |
6957577 | Firmin | Oct 2005 | B1 |
6980940 | Gurpinar et al. | Dec 2005 | B1 |
7062420 | Poe, Jr. | Jun 2006 | B2 |
7069148 | Thambynayagam et al. | Jun 2006 | B2 |
7079952 | Thomas et al. | Jul 2006 | B2 |
7134496 | Jones et al. | Nov 2006 | B2 |
7299131 | Tabarovsky et al. | Nov 2007 | B2 |
7363162 | Thambynayagam et al. | Apr 2008 | B2 |
7369979 | Spivey | May 2008 | B1 |
7774140 | Craig | Aug 2010 | B2 |
7890264 | Elphick | Feb 2011 | B2 |
20020050993 | Kennon et al. | May 2002 | A1 |
20020099505 | Thomas et al. | Jul 2002 | A1 |
20030047308 | Hirsch et al. | Mar 2003 | A1 |
20030132934 | Fremming | Jul 2003 | A1 |
20030216897 | Endres et al. | Nov 2003 | A1 |
20040006429 | Brown | Jan 2004 | A1 |
20040111216 | Kneissl et al. | Jun 2004 | A1 |
20040117121 | Gray et al. | Jun 2004 | A1 |
20040138819 | Goswami et al. | Jul 2004 | A1 |
20040153437 | Buchan | Aug 2004 | A1 |
20040220846 | Cullick et al. | Nov 2004 | A1 |
20050043892 | Lichman et al. | Feb 2005 | A1 |
20050049838 | Danko | Mar 2005 | A1 |
20050114031 | Thambynayagam et al. | May 2005 | A1 |
20050149307 | Gurpinar et al. | Jul 2005 | A1 |
20060069511 | Thambynayagam et al. | Mar 2006 | A1 |
20060129366 | Shaw | Jun 2006 | A1 |
20060184329 | Rowan et al. | Aug 2006 | A1 |
20060197759 | Fremming | Sep 2006 | A1 |
20070112442 | Zhan et al. | May 2007 | A1 |
20070112547 | Ghorayeb et al. | May 2007 | A1 |
20080162099 | Velasquez | Jul 2008 | A1 |
20080183451 | Weng et al. | Jul 2008 | A1 |
20080306892 | Crossley et al. | Dec 2008 | A1 |
20090084544 | Caldera | Apr 2009 | A1 |
20090084545 | Banerjee et al. | Apr 2009 | A1 |
20090234584 | Casey et al. | Sep 2009 | A1 |
20090276156 | Kragas et al. | Nov 2009 | A1 |
20090312996 | Guyaguler et al. | Dec 2009 | A1 |
20100145667 | Niu et al. | Jun 2010 | A1 |
Number | Date | Country |
---|---|---|
2309562 | Jul 1997 | GB |
2336008 | Oct 1999 | GB |
9964896 | Dec 1999 | WO |
2004049216 | Jun 2004 | WO |
2005122001 | Dec 2005 | WO |
Number | Date | Country | |
---|---|---|---|
20080120076 A1 | May 2008 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 11227540 | Sep 2005 | US |
Child | 11924560 | US |