Patent Description:
<CIT>, <CIT>, <CIT>, and <CIT> disclose processes for defining locations of wells in a field.

The process applies in particular for the design of wells in a field containing a hydrocarbon reservoir. It also applies in the design of carbon dioxide injection wells in carbon dioxide sequestration applications or in the design of water injection wells in hydrogeological applications. More generally, the method applies to any application in which one or more fluids are injected into or produced from a field in the subsoil.

The positioning of wells is a critical task in the production of a field containing a hydrocarbon reservoir. Indeed, the respective positions of producer wells and/or of injector wells, is a factor which may greatly affect the productivity of the field and the volume of hydrocarbon recovered, hence its profitability.

A numerical gridded model of the field is often generated to determine the properties of the reservoir contained in the field, including geology, infrastructure, and fluid properties.

Based on this model and on raw field data, a team of scientists determine the best potential locations for wells, usually based on experience, taking into account the constraints which exist in the field, such as distance to surface well head clusters or platforms. Key design parameters include spacing between wells, well drain length and well configurations. This process is time consuming and requires significant human effort and skill.

Software products have been developed to help positioning wells relative to the reservoir. These software products are usually based on calculations of geographic coordinates of the wells. Each well to be positioned is usually defined by a set of three coordinates for each end of the well drain (i. e the fraction of the well length where flow occurs between the reservoir and the wellbore). Therefore, the software must optimize at least six parameters per well. For a set of fifteen wells, the number of parameters raises to ninety, which becomes costly and lengthwise to solve, if possible.

In order to overcome this drawback, methods have been developed to improve well positioning, while decreasing the required resources in terms of computers or human force, by notably reducing the number of variables to be optimized.

For example, <CIT> discloses a process of positioning wells in a field comprising calculating a reservoir quality, and optimizing the position of the wells by maximizing the reservoir quality compared to the cost for drilling and completion. This process takes into account constraints which are fixed by the operators to position the wells.

Such a process reduces the quantity of calculations required for obtaining a definition of the wells locations. It nevertheless still requires a great number of variables to be solved.

One aim of the invention is to obtain a very efficient process for determining well positions in a field, which significantly reduces human input and improves computational time, while obtaining reliable results for improving productivity.

To this aim, the subject-matter of the invention is a process according to claim <NUM>.

The process according to the invention may comprise one or more of the features of claims <NUM> to <NUM> or of the following features, taken solely or according to any possible technical combination:.

The invention also relates to an electronic system according to claim <NUM> or <NUM>.

The invention also concerns a computer program product according to claim <NUM>.

The invention will be better understood upon reading of the following description, given solely as an example, and made in reference to the appended drawings, in which:.

A first process according to the invention is carried out for defining the locations of a plurality of wells <NUM>, <NUM> in a field <NUM> containing a fluid reservoir (see <FIG>). The fluid reservoir is located in a subsurface, onshore or offshore.

The reservoir generally contains at least a first fluid to be produced, and potentially a second auxiliary fluid to be produced along with the first fluid. A third fluid and/or a fourth fluid are advantageously used to be injected in the reservoir to drive the production of the first and/or of the second fluid.

For example, the first fluid is oil and/or gas, the second fluid being gas and/or oil. The third fluid and/or fourth fluid are generally water, gas, and/or oil. The first fluid and the second fluid are preferentially hydrocarbons.

The reservoir may comprise several regions, for example at least an aquifer, an oil leg, and a gas cap. An aquifer is generally delimited upwards by a water oil contact or "WOC". An oil leg is delimited between a water oil contact and a gas oil contact or "GOC". The gas cap is located above the gas oil contact.

The wells <NUM>, <NUM> to be positioned in the field <NUM> are producer wells <NUM> and injector wells <NUM>.

Producer wells <NUM> aim at the extraction of a desired fluid, i.e. the first fluid and/or the second fluid. Injector wells <NUM> are also positioned for injecting the third fluid and/or the fourth fluid to enhance the production of the desired fluid at the producer wells <NUM>.

The wells <NUM>, <NUM> can be positioned using different patterns. In a dispersed pattern, visible for example in <FIG>, injector wells <NUM> are located without preference for area of the reservoir where or close to where injected fluid is originally present. On the contrary, in a peripheral pattern, such as shown in <FIG>, injector wells <NUM> are located with a preference for areas of the reservoir where or close to where injected fluid is originally present. The well positioning pattern can be mixed, i.e. be peripheral relative to injectors injecting a particular fluid and dispersed relative to other types of injectors injecting a second type of fluid.

The field <NUM> is numerically simulated using a geocellular model <NUM> which is schematically illustrated on <FIG> as a two-dimensional grid.

The geocellular model <NUM> comprises at least one, or sometimes several sets of model realizations, each set containing typically a unique 2D, or 3D grid geometry made of a geocellular grid. The grid geometry is advantageously structured, i.e. follows a geometrical pattern. In a variant, the grid is unstructured.

The grid comprises a plurality of cells <NUM>. Each cell <NUM> has a specific geographical position in the model, defined by geographical coordinates. Each cell <NUM> moreover has a shape and a volume.

The model for example comprises more than <NUM> cells <NUM> and generally between <NUM><NUM> cells <NUM> and <NUM><NUM><NUM> cells <NUM>.

Each cell <NUM> is associated with cell infilling properties, which characterize the content of the cell <NUM>, as well as the properties of the fluid contained in the cell <NUM> when applicable.

The cell properties are usually chosen among the net to growth (NTG), the porosity Phi, the total compressibility Ct, the initial saturation in the considered fluid phase Si, the minimum saturation Sm in the considered phase during reservoir flow, the permeability K defined as a XYZ tensor property, K in each direction i = X, Y , Z being noted Ki, a relative permeability, Kr at or behind front for a given injection phase which is also defined as a XYZ tensor property, Krg designating a relative permeability to gas, Krw designating a relative permeability to water and Krwg relative permeability to co-injection of water gas.

Each cell <NUM> is also characterized by a diffusive pressure propagation slowness Slow, which is a tensor property, by a movable accumulation Accu, which can be defined for the fluid targeted for production and noted AccuP and which can be defined for the fluid targeted for injection as AccuL.

Each cell <NUM> has general dimensions DX, DY, DZ which can be averaged. Each cell <NUM> is connected to another cell <NUM>. Inter-cell properties can be defined by a transmissibility between cells <NUM>.

In the model <NUM>, the fluid properties of each cell <NUM> are advantageously defined by at least a cell infilling property representative of a fluid density and by at least a cell infilling property representative of an ability of a fluid to flow.

A first cell infilling property is advantageously a diffusive slowness Slow, which can be considered on an anisotropic (XYZ tensor) or on a isotropic basis. In a typical form, the slowness Slow in each cell <NUM> is equal to: <MAT>.

Variants include degenerated or inflated form of the typical form.

A second cell infilling property is a movable accumulation indicator Accu. In a typical form, the accumulation indicator is equal to: <MAT>.

Variants include degenerated or inflated forms of the typical form.

Another cell infilling property is a dimensionless indicator of the ability of a particular fluid to flow in or out of the wells or on/into/towards neighboring wells. In the typical form, the volume weight mean transmissibility Trans in the three-direction can be written as: <MAT>.

Alternatively, a property equal, in each cell <NUM>, to the sum of the transmissibility of all connections to the considered cell <NUM> divided by the cell volume, or any other indicator of the ability to flow into wells or towards neighboring cells could be used.

The model <NUM> is for example an assembly of data obtained from a simulation done in a commercial reservoir modeling simulator such as ECLIPSE or IX (INTERSECT) from SCHLUMBERGER, STARS and IMEX from CMG, or any similar product.

In the process according to the invention, each well <NUM>, <NUM> is defined within the model by at least one well location cell which is referred to as a well insertion point <NUM> (see for example <FIG>).

Advantageously, each well <NUM>, <NUM> is defined by a well drain, which is the part of a well which is producing from or injecting into the reservoir. Well drains can be positioned serially along a common trajectory or in parallel manners. The well drain is defined as a series of consecutive intervals joining cells <NUM> in which flow between the reservoir and the well occurs.

At minimum, one well insertion point <NUM> and one predefined drain length, such as a maximum drain length or a half drain length are enough to define a well drain in the process according to the invention. The predefined drain length is an input of the process.

For example, the well insertion point <NUM> is chosen as the center of the well drain. The predefined drain length is then a maximum half drain length between the drain center and drain ends, defined respectively as toe <NUM> and heel <NUM> of the well (see <FIG>).

In a variant, the well insertion point <NUM> is at one end of the well, the predefined drain length being a maximum full length of the well drain.

In both cases, the well <NUM>, <NUM> is defined in the model by a linear segment between the toe <NUM> and the heel <NUM>.

In another embodiment, the exact path of the well drain is defined from a first well insertion point <NUM>, by determining other well insertion points <NUM> of the same well <NUM>, <NUM>.

Optionally, one or more well geometry constraints can be defined as inputs of the process, such as a maximum curvature of the well <NUM>, <NUM>, a maximum depth of interval splitting algorithm, or another trajectory constraint feasibility function accepting as an input a set of trajectory points and returning a Boolean indicating whether the set of points represents a feasible trajectory.

Optionally, an additional constraint can be a typical maximum distance between well drains, if the additional drains belonging to the same well are provided.

The process according to the invention is carried out in a system <NUM> schematically represented in <FIG>.

The system <NUM> generally comprises at least a calculator <NUM> provided with at least one processor <NUM>, and at least one memory <NUM> containing software modules configured to be executed by the processor <NUM>.

The system <NUM> further comprises a display <NUM> and a man-machine interface <NUM> generally embodied as a keyboard, a mouse and/or a touch screen.

According to the invention, the memory <NUM> contains at least a software module <NUM> for acquiring to the calculator <NUM> a geocellular model <NUM> of the field <NUM>, as defined above. The memory <NUM> comprises a software module <NUM> for selecting a group of potential cells among cells <NUM> of the model <NUM>.

The memory <NUM> contains a software module <NUM> for positioning wells <NUM>, <NUM> one after another in the group of potential cells, the software module <NUM> comprising a plurality of software applications <NUM> to <NUM> for calculating individual insertion point drivers.

The software module <NUM> for positioning wells <NUM>, <NUM> one after another further comprises a software application <NUM> for determining a combined insertion point driver based on the individual insertion point drivers obtained by executing software applications <NUM> to <NUM> and a software application <NUM> for defining at least a well insertion point <NUM> based on the maximized combined insertion point driver determined by the software application <NUM>.

The software module <NUM> is for example able to acquire data relative to at least one realization of the model <NUM> obtained by a reservoir modeling simulator. Each model realization includes the definition of the cells <NUM> of the grid, and at least the cell infilling properties associated with each cell <NUM>.

The software module <NUM> for selecting a group of potential cells is able to determine, among the cells <NUM> of each model realization, a group of cells <NUM> in which a well insertion point <NUM> can be defined, and to exclude cells in which a well insertion point <NUM> cannot be defined. Cells in which a well position cannot be defined include for example cells already containing a well, or inaccessible cells given predefined constraints, such as geometrical constraints. Advantageously, the software module <NUM> is able to provide a Boolean indicator to each cell <NUM>, the Boolean indicator being <NUM> when the cell <NUM> belongs to the group of potential cells, the Boolean indicator being <NUM>, when the cell <NUM> is excluded.

The software applications <NUM> to <NUM> include at least a software application <NUM> for calculating at least a fluid property insertion point driver DFP1, DFP2, and at least a software application <NUM> for calculating at least a maximized distance insertion point driver DMD1, DMD2, DMD3.

The software applications <NUM> to <NUM> also optionally include a software application <NUM> for calculating an optimal distance insertion point driver DOD1.

In case a detailed path of the well <NUM>, <NUM> is determined, the software applications <NUM> to <NUM> also comprise a software application <NUM> for calculating a local insertion point driver DL1 for determining a local path of the well drain.

The software application <NUM> for calculating at least a fluid property insertion point driver DFP1, DFP2 is usually configured for calculating at least two fluid property insertion point drivers, respectively relative to the maximization of a fluid density parameter DFP1 and to the maximization of a fluid flow parameter DFP2.

The fluid property insertion point driver DFP1 aims at determining the cells <NUM> where there is a high spatial density of the fluid to be produced or injected. The fluid property insertion point driver DFP2 aims at determining the cells <NUM> where the well to reservoir flow and the reservoir cell to cell flow are easiest for a given phase.

The fluid property insertion point drivers DFP1 DFP2 are generally representative of a fluid property maximization. Preferentially, the fluid property insertion point drivers DFP1, DFP2 are calculated based on a local average density of a given fluid property.

The given fluid property is typically a property reflecting fluid density for fluid property insertion point driver DFP1 or a property reflecting ability of a fluid to flow for fluid property insertion point driver DFP2.

In a particular embodiment, the fluid property reflecting fluid density for fluid property insertion point driver DFP1 is a movable accumulation indicator for a particular phase, as defined above. The fluid property reflecting the ability of the fluid to flow for fluid property insertion point driver DFP2 is a transmissibility.

Advantageously, the fluid property insertion point drivers DFP1, DFP2 are calculated for each cell <NUM> using a window average of the fluid property around the cell <NUM> in question. For example, the window average is a decreasing moving average taken in at least two directions from the cell <NUM> in question.

In particular, the moving average is a normalized exponential moving average (NEMA3D) in three-dimensions. In a structured grid, a normalized exponential moving average is a filter that sums, along predefined directions (typically six [I+,I-,J+,J-,K+,K-] directions in structured grids as shown in <FIG>), the result of an exponential moving average filter that applies weighting factors which decrease exponentially in the considered direction.

In each direction, the weighing for each successive datum decreases exponentially, never reaching zero, as shown in <FIG>.

In a variant applicable to structured grids, a smaller subset of directions (e.g. the up, or down direction, particularly suitable in gravity drainage settings) can be used. On the contrary, adding diagonal directions basically launching rays going through series of corresponding cell edges, as shown in <FIG>, and/or launching rays along vertices directions, as shown in <FIG>, can be used.

The software application <NUM> is configured to scan all cells <NUM> of the group of potential cells and to calculate, for each cell <NUM>, the value of the or each fluid property insertion point driver DFP1, DFP2.

The software application <NUM> for calculating a maximized distance insertion point driver DMD1, DMD2, DMD3 is able to calculate at least one maximized distance insertion point driver DMD1, DMD2, DMD3, preferentially several maximized distance insertion point drivers DMD1, DMD2, DMD3 determining a maximum distance from a cell or a group of cells having undesired properties for the well <NUM>, <NUM> currently being positioned.

At least a maximized distance insertion point driver DMD1, DMD2 is determining well cells which are far from cells containing totally or partially a fluid phase which production from or injection into is not desired. A maximized distance insertion point driver DMD3 is determining cells being far from any well of the same type as the well <NUM>, <NUM> currently being positioned.

Each maximized distance insertion point driver DMD1, DMD2, DMD3 is calculated for each cell <NUM> by determining a distance to the cell or group of cells with undesired properties.

The distance is for example an Euclidian distance between the cell <NUM> and the cell or group of cells with undesired properties. In a variant, the distance is a cell count distance from the cell <NUM> to the cell or group of cells with undesired properties.

Preferentially, according to the invention, each maximized distance insertion point driver DMD1, DMD2, DMD3 is calculated based on a diffusive time of flight (TOF) from the cell <NUM> to the cell or group of cells with undesired properties. The diffusive time of flight is for example defined as the time of arrival at the cell or group of cells with undesired properties of a pressure wave in a porous medium from a source point being located at the cell <NUM>.

The diffusive time of flight can be easily calculated based on the slowness and geometry of each cell between the cell <NUM> and the cell or group of cells with undesired properties as described for example in the following publication:
https://en. org/wiki/Level_set_method?oldid=<NUM>.

In one advantageous embodiment, the cell or group of cells with undesired property is a fluid interface. In particular, the fluid interface is a water oil contact (WOC) or a gas oil contact (GOC), as defined above. When the cell or group of cells is an interface, the distance to such interface can be computed in either of the two regions that the interface delimitates. The calculation of the driver is carried out only in one of the two regions with the other region being attributed a zero distance value.

The calculation of time of flight can be made using a phase specific slowness and/or on a non-phase specific slowness as calculated above.

The software application <NUM> is configured to scan all cells <NUM> of the group of potential cells and to calculate, for each cell <NUM>, maximized distance insertion point drivers DMD1, DMD2, DMD3 for each scanned cell <NUM>.

As defined above, the software for calculating an optimized distance <NUM> is able to calculate at least an optimal distance insertion point driver DOD1 related for example to an optimal distance to a well <NUM>, <NUM> of a different type than the well <NUM>, <NUM> being positioned.

The optimal distance insertion driver DOD1 is calculated as a maximized distance insertion point driver such as DMD1 or DMD2, by applying a |D-X| transform, where the optimal distance D is an input of the process.

In an advantageous variant, the optimal distance D is determined from the reservoir model along a well pattern scale process. In that case, the software application <NUM> is able to calculate, for each well <NUM>, <NUM> being currently positioned, an optimal distance D based on a distance to existing producer wells <NUM> and based on an accumulation of the produced phase calculated per cell.

The optimal distance D is calculated depending on the setting of the wells. In a dispersed setting, the software application <NUM> is configured to compute the distance to existing producer wells, and then to compute, for each cell <NUM>, the fraction of the accumulation of the produced phase to the total accumulation of the produced phase as a function of the distance to existing producer wells <NUM>. Then, the software application <NUM> is able to determine the optimal distance D as equal to the maximum distance at which the accumulation fraction is equal or lower to the fraction FEP of the number of existing producer wells when the current well is being positioned incremented by one unit to the total number of producer wells <NUM> intended to be positioned. The fraction FEP can optionally be multiplied by a constant factor, comprised for example between <NUM> and <NUM>.

In a peripheral setting, the software application <NUM> is configured to compute a distance of each cell <NUM> to existing producer wells <NUM>, then, to sort the accumulation per cell of the produced phase according to the above-computed distance to a producer wells <NUM>, and then to sort the accumulation per cell of the produced and injected phase according to the above-computed distance to producer wells <NUM>.

The software application <NUM> is then configured to accumulate the produced phase from low to high distance and to cumulate the produced plus injected phase from low to high distance.

The optimal distance D is then defined by the software application <NUM> as the lowest distance, multiplied by a constant, for which the accumulation ratio between cumulated produced fluid divided by cumulated produced plus injected fluid falls below a predefined threshold.

For example, the constant is chosen to be <NUM> to <NUM>. The predefined threshold is for example in the range of <NUM> to <NUM> in a setting in which the oil saturation is constant at <NUM> in the oil leg, and water saturation constant at <NUM> in the oil leg and equal to <NUM> in the water leg. In such situation the cumulated accumulation ratio will be equal to <NUM> for short distance from wells situated in the oil leg and will progressively diminish towards <NUM> for distances such as to include portions of the water leg.

In an alternate embodiment, the optimal distance D is defined by the software application <NUM> as the mean distance at the contact between the injected and produced fluid. The method is then faster to operate.

The optimal distance insertion driver DOD1 is calculated for each cell <NUM> by the software application <NUM> using an Euclidian distance, a cell count distance and preferentially a diffusive time of flight, as defined above.

The software application <NUM> is configured to be executed when the particular path of a well drain has to be determined, once at least one insertion point <NUM> of a well <NUM>, <NUM> being positioned has been defined.

The software application <NUM> is configured to calculate a local insertion point driver DL1 to maximize the distance to insertion points already defined for the well <NUM>, <NUM> being currently positioned. This maximized distance is an Euclidian distance, a cell count distance or preferentially a diffusive time of flight, as defined above.

The software application <NUM> is configured to calculate the local insertion point driver DL1 only for cells of a local insertion region <NUM> (see <FIG>) defined within the predefined drain length distance (e.g. the maximum half drain length distance) of the previously defined center of the well drain. The local insertion point driver DL1 is defined in reference to the insertion points <NUM> already defined for the well being currently positioned.

The software application <NUM> is configured to determine a combined injection point driver DCOMB based on at least one fluid property insertion point driver DFP1, DFP2, and on at least one maximized distance insertion point driver DMD1, DMD2, DMD3.

Preferentially, it is able to calculate the combined insertion point driver DCOMB also based on an optimization distance insertion point driver DOD1 and/or with a local insertion point driver DL1, when determining further well insertion points of a well being positioned.

Advantageously, the combined insertion point driver DCOMB is a product of several insertion point drivers, each multiplied by a constant Ci and/or brought to a specific power Ei. The following equation gives an example of calculation of DCOMB using <NUM> insertion point drivers: <MAT>.

The number of insertion point drivers used for calculating the combined insertion point driver DCOMB can be decreased or increased depending on the context. The number of insertion point drivers is generally comprised between <NUM> and <NUM>, in particular between <NUM> and <NUM> when positioning a first insertion point <NUM> of a well <NUM>, <NUM>, and between <NUM> and <NUM> when positioning a further insertion point <NUM> of the same well <NUM>, <NUM>.

The software application <NUM> is configured to define at least a well insertion point <NUM> as a well location cell of a well <NUM>, <NUM> being currently positioned in the model by selecting among the group of potential cells, the cell <NUM> which displays the maximal combined insertion point driver DCOMB. In case several locations are equally maximal, the insertion point <NUM> can be determined either on a neighbored analysis method which will be described below or alternatively, by random choice or by other predefined criteria such as the minimal or maximal cell index among equally maximum cells.

A method according to the invention, using the system <NUM> according to the invention, will be now described. The method will be described for example for the determination of the positions of several producer wells <NUM> and several injector wells <NUM> in a field <NUM> characterized by one realization of a geocellular model <NUM> of the field <NUM>.

The process first comprises a step of acquiring by the calculator <NUM> the model realization of the geocellular model <NUM> of the field. As explained above, the model <NUM> defines a plurality of cells <NUM>, each cell <NUM> being characterized by fluid properties as defined above, in particular a slowness Slow, a movable accumulation indicator Accu and a volume weight mean transmissibility Trans in the three-directions.

The calculator <NUM> advantageously lets the user select the different constraints as defined above using the man/machine interface <NUM>. This includes in particular the half drain maximum length or full drain length and/or the above-defined geometrical constraints.

The user also selects a number of wells <NUM>, <NUM> for each well type, and a type of well pattern.

Based on this selection, the calculator <NUM> determines the type of well <NUM>, <NUM> to be inserted next. The order for inserting wells <NUM>, <NUM> is defined as a function of the well pattern which has been selected by the user for the concerned fluid. For example, producer wells <NUM> are always part of a dispersed setting.

In a peripheral setting, wells <NUM>, <NUM> are introduced per well types. The order of the well types is defined according to a typical well type ordering following the following rules :.

In a dispersed setting, wells <NUM>, <NUM> are introduced one by one starting with the well types that would minimize the difference between the current and target well type proportions. The target proportions are computed at the perimeter of the dispersed well types. In case of equality, the next well to be introduced is selected based upon well type as defined above.

In any case, the wells <NUM>, <NUM> are positioned one after the other. The positioning of a subsequent well <NUM>, <NUM> only occurs when the positioning of a former well <NUM>,<NUM> has been completed and taken into account in the model <NUM>.

For each well <NUM>, <NUM> being inserted, the process then comprises a selection by the software module <NUM> of a group of potential cells able to become a well location.

Then, as shown in <FIG>, for each cell <NUM> of the group of potential cells, the process comprises a step <NUM> of calculation of several or all insertion point drivers among the insertion point drivers DFP1, DFP2, DMD1, DMD2, DMD3, DOD1, DL1 by the relevant software applications <NUM> to <NUM> to determine at least a first insertion point of the well currently being positioned.

As mentioned above, at least one fluid property insertion point driver DFP1, DFP2 representative of a fluid property maximization is calculated for each cell <NUM>. Advantageously, two fluid property insertion point drivers DFP1, DFP2 are calculated by software application <NUM> to determine the cells <NUM> having maximized fluid density and maximized fluid flow.

The software application <NUM> calculates the or each fluid property insertion point driver DFP1, DFP2 of each cell <NUM> advantageously based on a window average of the fluid property around the cell <NUM>, preferentially based on a decreasing moving average in at least two directions and more preferentially based on a normalized exponential moving average, as described above.

Advantageously, the two fluid properties used for calculating the two fluid property insertion point drivers DFP1, DFP2 are respectively an accumulation Accu in one phase and a transmissibility Trans, as defined above.

The software application <NUM> calculates at least one maximized distance insertion point driver DMD1, DMD2, DMD3 for each cell <NUM> characterizing a distance maximization to another cell or group of cells with an undesired property.

Preferentially, the cell or group of cells having undesired properties are cells totally or partially containing a fluid phase which production from or injection into is not desired or are cells or groups of cells of any well of the same type than the well being positioned.

In particular, the software application <NUM> calculates a maximum distance from each cell <NUM> to a fluid interface, for example a WOC or a GOC.

Preferentially, the distance is calculated based on a diffusive time of flight as mentioned above, using a cell slowness and geometry for each cell on the path between the cell <NUM> and the cell or group of cells having undesired properties.

The software application <NUM> optionally calculates an optimized distance insertion point driver DOD1 based on an optimal distance D to wells of a different type than the well being positioned.

The optimal distance D is either predefined by the user, for example using the man/machine interface <NUM> or is computed directly by the software application <NUM> for each well being positioned, as described above, depending on the chosen setting (dispersed setting or peripheral setting), on a distance to existing producer wells <NUM> and/or on accumulation of the produced phase for each cell.

As shown in step <NUM> in <FIG>, once each fluid property insertion point driver DFP1, DFP2, DMD1, DMD2, DMD3, DOD1 being used has been calculated for each cell <NUM>, each insertion point driver value obtained for each cell <NUM> is normalized relative to the maximal value of the same insertion point driver among the cells <NUM> of the group of potential cells.

Then, as shown in step <NUM>, the software application <NUM> calculates a combined insertion point driver DCOMB for each cell <NUM>, for example according to the above-mentioned equation (<NUM>), each multiplied by a predefined tunable constant Ci and/or brought to a predefined tunable power Ei.

As shown in step <NUM>, the software application <NUM> for defining a well location cell then identifies the cell <NUM> having the maximum combined insertion point driver value, which constitutes a first well insertion point <NUM>. The first insertion point <NUM> is usually considered the well center of the well <NUM>, <NUM> being positioned.

If no predefined half drain length or local insertion point driver has been provided, the well <NUM>, <NUM> is defined as a single cell well and the process starts positioning a new well by repeating the above described steps.

If a predefined half drain length has been defined, the process comprises a definition typically of the two ends <NUM>, <NUM> of the well drain in a predefined order based on the predefined half drain length.

Alternatively, the first insertion point <NUM> is the toe <NUM> or heel <NUM> of the well <NUM>, <NUM> being positioned. The full drain length is used to determine the other end of the well.

As shown in step <NUM> of <FIG>, cells within the predefined drain length distance of the previously defined insertion point <NUM> are identified and grouped in a local insertion region <NUM>.

The software application <NUM> for calculating a local insertion point driver then calculates a local insertion point driver DL1 for each cell in the above-mentioned defined region <NUM>.

Then, the previous insertion point drivers DFP1, DFP2, DMD1, DMD2, DMD3, DOD1 for each of the cells <NUM> of the local insertion region <NUM>, determined at step <NUM>, are combined to the local insertion point driver LD1 to obtain a combined insertion point driver DCOMB (using equation <NUM>). The cell <NUM> maximizing the combined insertion point driver DCOMB is determined by the software application <NUM>.

The feasibility of the trajectory including the already positioned insertion points <NUM> of the current well <NUM>, <NUM> is checked. If feasible, the new point at cell <NUM> is added to the trajectory. If not feasible, the cell is removed from the local insertion region <NUM> and the local determination step <NUM> is re-iterated until there are no potential cells or a solution is found. If there are no cell left the process is deemed complete for the well <NUM>, <NUM> being positioned.

The above-mentioned well definition including all insertion points <NUM> of the well <NUM>, <NUM> is then inserted in the model.

The process is then re-iterated to position another well <NUM>, <NUM> until the numbers of wells <NUM>, <NUM> defined by the user have been positioned.

The process may comprise a subsequent step of displaying the positions of the wells <NUM>, <NUM> on a display such as display <NUM>. The positions of the wells <NUM>, <NUM> may then be used in a drilling operation to drill at least a well <NUM>, <NUM> in the field <NUM>.

Examples of insertion point driver policies are given in the following examples.

In such setting, the behavior can be finely tuned in a number of optional variants to balance the computational cost to quality of result ratio.

Slowness can be defined in a phase specific manner. This added complexity is unnecessary unless a large contrast exists across the well implantation area for the relative mobility to a given phase (which is very unlikely in oil and gas reservoir environments).

Would the water and oil saturation not vary significantly over the reservoir target, for speeding up or simplifying setup, pore volume is used rather than phase specific accumulation.

Phase specific transmissibility could be used particularly for injectors. This allows factoring the reduction of injectivity index for water injector wells completed in part or totality in oil compared to wells completed in the water leg.

In a dispersed setting, partially peripheral patterns can be built by introducing distance to WOC or distance to WOC with a predetermined offset as a maximized distance insertion point driver.

In a dispersed water injection / oil production setting, gas areas are avoided because of the impact of gas upon water injectivity and because gas area would typically be located above oil, thus determining an unfavorable situation relative to gravity forces.

In advantageous variants, the distance to the contact between the oil and the injected phase is computed in both the oil and injected phase regions and is given arbitrary signs (ex: positive within the injected phase region, negative outside).

Such a distance is advantageously modified by adding a positive offset distance value and then, setting negative values to zero. Using such a modified distance as positioning driver allows positioning injector wells in the oil zone within a fixed time of flight distance to the true contact while favoring wells further within the injected fluid region. The offset value is a predefined input defining the policy. It is for example comprised between <NUM> and <NUM> of the mean distance between the top of the structure and the water or gas contact.

In another variant, illustrated in <FIG>, the model <NUM> comprises several model realizations 120A to 120D. The software module <NUM> is able to provide several model realizations to the calculator <NUM>.

The process according to the invention differs from the process described for a single model realization of the model <NUM> in that for each well <NUM>, <NUM> being positioned, a location of the first insertion point <NUM> of the well <NUM>, <NUM> is calculated for each model realization 120A to 120D, using point insertion drivers DFP1, DFP2, DMD1, DMD2, DMD3, DOD1 according to the above-described steps <NUM> to <NUM>.

The result leads to a plurality of first potential first well insertion points 20A to 20D, each insertion point 20A to 20D corresponding to a realization 120A to 120D of the model <NUM> (<FIG>).

Then, in <FIG> the calculator <NUM> determines a location presenting the highest density of possible insertion points 20A to 20D by executing the location determination method disclosed schematically in <FIG>.

The location determination method comprises defining an initial maximum value as a negative infinite.

Then, the method comprises scanning all cells <NUM>, checking if cell value is greater than maximum, and if so, updating maximum.

The method then comprises scanning all cells <NUM> and building a group of cells (region R) where insertion point density is maximal. An adjacency depth factor is initialized to zero. For every cell in the region R defined previously, the method comprises computing the average density across all cells <NUM> adjacent within the current depth factor to the considered cell.

The adjacency depth is defined as the minimum number of adjacent cells connecting two cells. The group of cell "adjacent with depth zero" to a given cell is limited to the considered cell, the group of cells "adjacent at depth one" to a given cell correspond to the considered cell and its neighbors, the group of cells "adjacent at depth <NUM>" corresponds to the neighbors of neighbors and cells adjacent at depths <NUM> and <NUM>, and so forth.

The method comprises scanning all cells <NUM> in region R to determine a maximal average density and identifying all cells <NUM> in region R which average density is maximal. The method then comprises redefining R to such region.

If the number of cells in region R is one, the cell location is the well insertion point <NUM>. If not, if the width is such to include all model cells then return the cell location closest to the mean geographic cell location of all cells in the region initially defined above. Else, the method increments the adjacency depth factor by one and loop back to computing the average density across all cells adjacent within the current depth factor to the considered cell until a well location point <NUM> is determined (<FIG>).

Then, in reference to <FIG>), at least another first insertion point <NUM> of another well <NUM>, <NUM> is determined as described above. For determining the other first insertion point of the other well, the position of the insertion points <NUM> of the previously positioned wells <NUM>, <NUM> such as the first well <NUM>, <NUM> is kept the same in each model realization 120A to 120D.

The process of determining a well position for each subsequent well <NUM>, <NUM> is then reiterated, keeping constant the positions of each well <NUM>, <NUM> already positioned (<FIG>).

Thanks to the process according to the invention, a quick and accurate positioning of a plurality of wells <NUM>, <NUM> in a field <NUM> is obtained. The process is very efficient in terms of numbers of used variables, since a typical form of the process requires only seven drivers, for the simple problem of positioning a single linear well drain (scaling factors for distance to WOC, GOC, inter-well distance, movable accumulation indicator and transmissibility, and maximum distance between well center and well ends).

This has to be compared to the geographic formulation, which requires three geographic coordinates multiplied by two well ends <NUM>, <NUM>, i.e. <NUM> total parameters multiplied by the number of wells.

For example for fifteen wells <NUM>, <NUM>, the ratio of parameters diminishes from <NUM> to <NUM> in the process according to the invention. The process according to the invention greatly reduces the computational time required for optimizing well patterns. Moreover, the process by nature points to the most relevant areas for positioning the wells <NUM>, <NUM> in the field <NUM>, hence reducing human working time required for building well patterns and improving performance of the resulting well pattern.

In particular, when time of flight is used as a measurement of distance, the accuracy of the obtained results is greatly improved, while the computational needs remain quite low. The use of a moving average around each cell <NUM> also allows a quick and accurate determination of the fluid density insertion point drivers.

Claim 1:
Process for defining the locations of a plurality of wells (<NUM>, <NUM>) in a field (<NUM>), the process being carried out by an electronic location defining system (<NUM>) and comprising the following steps:
- acquiring a geocellular model (<NUM>) of the field (<NUM>), the model (<NUM>) defining a plurality of cells (<NUM>), each cell (<NUM>) being provided with fluid properties including at least a fluid density property and at least a fluid flow property for at least two fluid phases ;
- selecting a group of potential cells (<NUM>) able to become a well location;
characterized by positioning wells (<NUM>, <NUM>) one after another in the group of potential cells (<NUM>), each positioning of a well (<NUM>, <NUM>) comprising:
* calculating for each cell (<NUM>) of the group of potential cells, at least one fluid property insertion point driver (DFP1, DFP2) representative of a fluid property maximization, the fluid property insertion point driver (DFP1, DFP2) being calculated based on a window average of the fluid property taken around the cell (<NUM>) ;
* calculating for each cell (<NUM>) of the group of potential cells, at least one maximized distance insertion point driver (DMD1, DMD2, DMD3) representative of a maximization of a distance to another cell or group of cells having at least an undesired property, the undesired property being chosen among a cell containing a fluid phase which production from or injection into is not desired or a cell containing a well of the same type that the well (<NUM>, <NUM>) being positioned, the at least one maximized distance insertion point driver (DMD1, DMD2, DMD3) being calculated for each cell (<NUM>) based on a diffusive time of flight from the cell (<NUM>) to the cell or group of cells having undesired properties ;
* calculating for each cell (<NUM>) of the group of potential cells a combined insertion point driver (DCOMB) based on the at least one fluid property insertion point driver (DFP1, DFP2) and the at least one maximized distance insertion point driver (DMD1, DMD2) ;
* defining a well insertion point (<NUM>) of the well (<NUM>, <NUM>) being positioned at the cell (<NUM>) having a maximal combined insertion point driver (DCOMB).