WO2025159755A1

WO2025159755A1 - Target trajectory for geosteering drilling of a wellbore

Info

Publication number: WO2025159755A1
Application number: PCT/US2024/013015
Authority: WO
Inventors: Tingting Zeng; Siyang SONG; Robert P. Darbe; Eirik HANSEN
Original assignee: Halliburton Energy Services Inc
Current assignee: Halliburton Energy Services Inc
Priority date: 2024-01-25
Filing date: 2024-01-26
Publication date: 2025-07-31
Anticipated expiration: 2026-07-25
Also published as: US20250243710A1

Abstract

A method comprises retrieving geoscience data of a subsurface formation into which a wellbore is being drilled and retrieving drilling operation data for drilling the wellbore. The method includes determining at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data. The method includes modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations.

Description

TARGET TRAJECTORY FOR GEOSTEERING DRILLING OF A WELLBORE BACKGROUND [0001] Drilling of a wellbore may include geosteering operations to guide the drilling operation accurately through the subsurface formation to reach a specific target. For example, geosteering may be used to guide the drilling to a hydrocarbon reservoir in the subsurface formation for recovery of such hydrocarbons. [0002] In a geosteering operation, a well-defined well plan that a drill bit may follow is an important component of many geoscience workflows. However, during a geosteering operation, different factors may cause the drill bit to veer off from a given well plan. Examples of such factors may include subterranean conditions, drilling operations, etc. BRIEF DESCRIPTION OF THE DRAWINGS [0003] Embodiments of the disclosure may be better understood by referencing the accompanying drawings. [0004] FIG.1 is a perspective view (partially cross sectional) of an example well system, according to some embodiments. [0005] FIG.2 is a block diagram of an example computer, according to some embodiments. [0006] FIG.3 is a cross-sectional view of an example reservoir in a subsurface formation that includes example wellpaths, according to some embodiments. [0007] FIG.4 is a block diagram of an automated workflow for wellbore target trajectory planning and geosteering for drilling a wellbore, according to some embodiments. [0008] FIG.5 is a block diagram of a first example flowchart for wellbore target trajectory planning and geosteering for drilling a wellbore, according to some embodiments. [0009] FIG.6 is a graph of example soft and hard constraints of a wellbore planning trajectory along a true vertical depth of a wellbore, according to some embodiments. [0010] FIG.7 is a block diagram of a second example flowchart for wellbore target trajectory planning and geosteering for drilling a wellbore, according to some embodiments. [0011] FIG.8 is a graph of an example of when at least one attribute of the geoscience model has gained sufficient changes to trigger an event, according to some embodiments. [0012] FIG.9 is a graph of an example of when a scoring mechanism is to trigger an event, according to some embodiments. DESCRIPTION [0013] The description that follows includes example systems, methods, techniques, and program flows that embody aspects of the disclosure. However, it is understood that this disclosure may be practiced without these specific details. In some instances, well-known instruction instances, protocols, structures, and techniques have not been shown in detail in order not to obfuscate the description. [0014] Example implementations relate to wellbore drilling that include geosteering operations. Such implementations may include providing an updated well plan for a geosteering operation in response to different factors and conditions that cause deviation of a well plan as a wellbore is being drilled. Conventional approaches for updating a well plan during drilling may require significant time and expertise. Additionally, conventional approaches may lack a systematic method to automatically provide or revise a well plan. When updates to a well plan are implemented manually, planning a target trajectory has no performance guarantee. This is because such conventional approaches may heavily depend on a human’s experience, may violate some constraints or criteria, and most likely not provide an optimal solution. [0015] Example implementations may include a rigorous and repeatable method for wellbore target planning that may overcome the aforementioned limitations. Example implementations may include a novel workflow towards a programmed automatic wellbore target trajectory planning technique. Additionally, example implementations may include a workflow that may comprise programmed automatic wellbore target trajectory planning that is able to perform on its own without the needs for human intervention. [0016] Example implementations may be able to adapt to changes in factors such as subterranean conditions, drilling operation, etc. in real-time. Example implementations may use geoscience data and drilling operation data to automatically plan an optimal wellbore trajectory in response to the latest changes therein. Example implementations may include a target planner that may operate over both landing and horizontal sections. [0017] Additionally, the planned target trajectory may be robust to uncertainties that may occur in 1) the earth model, 2) geosteering interpretation, 3) measurements of the location of the well path, the drill bit, and the wellbore, and 4) steering operations and dynamics. Example implementations may provide the solution whenever it exists since the well planner may be formulated in a convex fashion. [0018] Conventional approaches to wellbore target planning rely on target waypoints as part of the input and need human intervention. In contrast, example implementations may include an automatic wellbore target trajectory planning technique. Also, example implementations do not need to rely on such waypoints or require human intervention. Requiring one or more waypoints essentially requires a user to have prior knowledge of where the solution is at a specific depth. [0019] A waypoint with regard to wellbore target planning and optimization of trajectory of the wellbore may be defined as a predetermined depth or location that the wellbore needs to intersect during its drilling. Waypoints may be used to guide the drilling process and ensure that the well is drilled according to the desired trajectory and objectives. Such waypoints may be input by a user as part of a conventional wellbore target planning for the trajectory of the wellbore. In some implementations, operations may be independent of or may not include use waypoints for wellbore target planning for optimization of trajectory of the wellbore. Such waypoints require prior knowledge of the direction and drilling of the wellbore. In some implementations, such prior knowledge is not required in order to optimize the trajectory of the wellbore. Example System [0020] FIG.1 is a perspective view (partially cross sectional) of an example well system, according to some embodiments. An illustrative geosteering environment is shown in FIG.1. A drilling platform 102 supports a derrick 104 having a traveling block 106 for raising and lowering a drill string 108. A top drive 110 supports and rotates the drill string 108 as it is lowered through the wellhead 112. A drill bit 114 is driven by a downhole motor and/or rotation of the drill string 108. As the drill bit 114 rotates, it creates a wellbore 116 that passes through various formations. A pump 118 circulates drilling fluid 120 through a feed pipe 122, through the interior of the drill string 108 to drill bit 114. The fluid exits through orifices in the drill bit 114 and flows upward through the annulus around the drill string 108 to transport drill cuttings to the surface, where the fluid is filtered and recirculated. [0021] The drill bit 114 is just one piece of a bottomhole assembly 124 that includes a mud motor and one or more “drill collars” (thick-walled steel pipe) that provide weight and rigidity to aid the drilling process. Some of these drill collars include built-in logging instruments to gather measurements of various drilling parameters such as position, orientation, weight-on-bit, borehole diameter, etc. The tool orientation may be specified in terms of a tool face angle (rotational orientation), an inclination angle (the slope), and compass direction, each of which can be derived from measurements by magnetometers, inclinometers, and/or accelerometers, though other sensor types such as gyroscopes may alternatively be used. In one specific embodiment, the tool includes a 3-axis fluxgate magnetometer and a 3-axis accelerometer. As is known in the art, the combination of those two sensor systems enables the measurement of the tool face angle, inclination angle, and compass direction. Such orientation measurements can be combined with gyroscopic or inertial measurements to accurately track tool position. [0022] Also included in bottomhole assembly 124 is a telemetry sub that maintains a communications link with the surface. Mud pulse telemetry is one common telemetry technique for transferring tool measurements to surface receivers and receiving commands from the surface, but other telemetry techniques can also be used. For some techniques (e.g., through-wall acoustic signaling) the drill string 108 includes one or more repeaters 130 to detect, amplify, and re-transmit the signal. At the surface, transducers 128 convert signals between mechanical and electrical form, enabling a network interface module 36 to receive the uplink signal from the telemetry sub and (at least in some embodiments) transmit a downlink signal to the telemetry sub. A computer 150 may receive a digital telemetry signal, demodulate the signal, and display the tool data or well logs to a user. Software (represented in FIG.1 as machine-readable media 152) may govern the operation of computer 150. For example, the machine-readable media 152 may include instructions executable by a processor within the computer 150. A user may interact with computer 150 and its machine-readable media 152 via one or more input devices 154 and one or more output devices 156. [0023] In some implementations, the processor of the computer 150 may execute instructions to perform operations for automatic wellbore trajectory planning and performing geosteering (as further described herein). Additionally, the processor may communicate with different components downhole. For example, the processor may communicate commands to different components the bottomhole assembly 124. For instance, the processor of the computer 150 may control the steering of the drill bit 114 along a desired path using any one of various suitable directional drilling systems, including steering vanes, a “bent sub”, a rotary steerable system etc. [0024] For example, for precision steering, the steering vanes may be the most desirable steering mechanism. The steering mechanism may be controlled downhole, with a downhole controller programmed to avoid, intersect, or follow the existing well at a predetermined distance and position (e.g., directly above or below the existing wellbore). The measurements needed for geosteering can be gathered using an electromagnetic logging tool that makes multi-component measurements. [0025] An example of the computer 150 is now described. FIG.2 is a block diagram of an example computer, according to some embodiments. FIG.2 depicts a computer 200 that includes a processor 201 (possibly including multiple processors, multiple cores, multiple nodes, and/or implementing multi-threading, etc.). The computer 200 includes a memory 207. The memory 207 may be system memory or any one or more of the above already described possible realizations of machine-readable media. The computer 200 also includes a bus 203 and a network interface 205. [0026] The computer 200 also includes a data processor 211and a controller 215. The data processor 211 and the controller 215 may perform one or more of the operations described herein. For example, the data processor 211 may perform data processing for determining wellbore trajectory planning. The controller 215 may perform various control operations to perform geosteering operations based on the wellbore trajectory planning. [0027] Any one of the previously described functionalities may be partially (or entirely) implemented in hardware and/or on the processor 201. For example, the functionality may be implemented with an application specific integrated circuit, in logic implemented in the processor 201, in a co-processor on a peripheral device or card, etc. Further, realizations may include fewer or additional components not illustrated in FIG.2 (e.g., video cards, audio cards, additional network interfaces, peripheral devices, etc.). The processor 201 and the network interface 205 are coupled to the bus 203. Although illustrated as being coupled to the bus 203, the memory 207 may be coupled to the processor 201. [0028] To help illustrate a wellbore target trajectory for geosteering drilling of a wellbore, FIG.3 is a cross-sectional view of an example reservoir in a subsurface formation that includes example wellpaths, according to some embodiments. FIG.3 depicts a cross-sectional view of a subsurface formation 300 that includes reservoir 302. For example, the reservoir 302 may include different types of hydrocarbons. The reservoir 302 includes boundaries 304 and 305. In this example, there are three wellpaths. A wellpath 306 is a wellpath within a certain zone of the reservoir 302. A wellpath 308 is a wellpath within the reservoir 302. A wellpath 310 is a wellpath close to the boundary 304. Example implementations may attempt to maintain the wellbore target trajectory at or near the wellpath 306 in order to maximize recovery of hydrocarbons from the zone of the reservoir 302. Example Operations [0029] Example operations for performing subsurface carbon sequestration using a sealing element are now described. FIG.4 is a block diagram of an automated workflow for wellbore target trajectory planning and geosteering for drilling a wellbore, according to some embodiments. FIG.4 depicts a workflow 400. The workflow 400 includes a geoscience model 402, a target planner 404, and a drilling operation 406. [0030] The geoscience model 402 may include different geoscience data. For example, the geoscience data may include (a) geophysical data such as seismic data; (b) geological data such as petrophysical data and facies classification; (c) geo-mechanical data such as pressure data, stress data; etc. Overall, the geoscience data should provide insight to the location of geological discontinuities, such as faults, and sedimentary layers as well as to the physical properties of rock such as type, porosity, and thickness of each sedimentary layer. [0031] The target planner 404 may include optimization of the trajectory of the drilling of the wellbore (as further described below). The drilling operation 406 may include the drilling of the wellbore based on the optimization of the trajectory of the drilling of the wellbore provided by the target planner 404. [0032] As shown, the data from one block may serve as input into another block and vice versa. Thus, the data from the geoscience model 402 may be inputted into the target planner 404 and the drilling operation 406. Conversely, the data from the target planner 404 and the data from the drilling operation 406 may be inputted into the geoscience model 402. The data from the target planner 404 may be inputted into the drilling operation 406. Conversely, the data from the drilling operation 406 may be inputted into the target planner 404. Each of these blocks of the workflow 400 are described in more detail below in reference to FIG.5 and FIG.7. [0033] FIG.5 is a block diagram of a flowchart for wellbore target trajectory planning and geosteering for drilling a wellbore, according to some embodiments. Operations of a flowchart 500 of FIG.5 are described with reference to FIGS.1-2. Operations of the flowchart 500 start at block 502 and block 504. [0034] At block 502, geoscience data for the subsurface formation through which the wellbore is being drilled is retrieved. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may retrieve the geoscience data for the subsurface formation through which the wellbore 116 is being drilled. The processor 201 may retrieve the geoscience data from various available sources (such as databases stored in machine-readable media, sensors that are positioned downhole in the wellbore 116, etc. This geoscience data may include (a) geophysical data such as seismic data; (b) geological data such as petrophysical data and facies classification; (c) geo-mechanical data such as pressure data, stress data; etc. Overall, the geoscience data may provide insight to the location of geological discontinuities, such as faults, and sedimentary layers as well as to the physical properties of rock such as type, porosity, and thickness of each sedimentary layer. Operations of the flowchart 500 continue at block 504. [0035] At block 504, the geoscience data for the subsurface formation through which the wellbore is being drilled is processed. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may process this retrieved geoscience data. In some implementations, processing this data may include summarizing subterranean formation, location that the wellbore should stay within or away from, etc. As part of processing of this geoscience data, factors that may be considered may include: (1) certain bed boundaries based on user’s specification, (2) avoidance of collision with obstacles such as previously drilled wells, drilling hazards, hard formations like rocks, etc. (3) maintaining certain distance from bed boundaries or water-oil- contact, and (4) staying at certain zones that maximize productivity within a hydrocarbon reservoir. Operations of the flowchart 500 continue at block 510. [0036] At block 506, drilling operation data for the wellbore being drilled is retrieved. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may retrieve the drilling operation data for drilling the wellbore 116. The processor 201 may retrieve the drilling operation data from various available sources (such as databases stored in machine-readable media, sensors that are positioned downhole in the wellbore 116, etc. For example, the processor 201 may retrieve historical drilling operation data from a previously drilled section of the current wellbore or from offset wells. Historical drilling data may include a wellbore path (that includes location, altitude, etc.), drill bit and hole information, dogleg severities, tool dynamics and wellbore dynamics, dynamic and/or static drilling parameters, etc. Historical drilling data may provide insight into how the wellbore path could possibly be drilled and basic operational limits while drilling a wellbore trajectory. Operations of the flowchart 500 continue at block 508. [0037] At block 508, the drilling operation data for the wellbore being drilled is processed. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may process the drilling operation data. In some implementations, processing this data may include summarizing operational parameter settings and limits. Factors that may be considered when processing the drilling operation data may include current location of the drill bit and hole location and wellpath, which should provide knowledge of the starting condition of the planned wellbore. Other factors may include knowledge of current tool dynamics and borehole dynamics based on tool settings and neighboring subterranean conditions. These factors may subsequently be used to define constraints such as kinematics constraints (e.g., dogleg severity), safety constraints, or velocity constraints (e.g., force, torque), or drag constraints that maximize ROP of a drill bit. Another factor that may be considered when processing the drilling operation data may include total depth that the wellbore is expected to reach within the hydrocarbon reservoir. Operations of the flowchart 500 continue at block 510. [0038] At block 510, a trajectory of well path is optimized based on the processed geoscience data and the processed drilling operation data. For example, with reference to FIGS. 1-2, the processor 201 of the computer 200 may perform this operation. The processor 201 may formulate a trajectory optimization problem based on the processed geoscience data and the processed drilling operation data. The formulated problem may be solved for a target trajectory over the planning horizon. In some implementations, the solution may contain any (independent) state required for steering controls and operations. [0039] Components for optimization of the trajectory, in accordance with example implementations, are now described. Thus, these components may be used when determining the optimal trajectory of the wellbore. These components may include: 1) cost function, 2) constraints, 3) initial condition, 4) sampling rate, and 5) planning horizon. [0040] The cost function of a wellbore target trajectory planning problem may be a combination of one or multiple of the following example cost functions. A first cost function may be a deviation from specific reference trajectory, if provided by a user for any reason. Examples of such deviations may include deviations from depth (stratigraphic depth, true vertical depth, relative depth, etc.), angular (inclination, azimuth), spatial (easting, northing), or a combination thereof. A second cost function may be smoothness and/or shape of the planned trajectory. For example, this may be in terms of dog-leg-severity, tortuosity, build rate, turn rate, or a combination thereof. A third cost function may include cost related terms such as drilling time (opposite to Rate of Penetration (ROP)), energy used to drill, bit wear, projected carbon emission, or a combination thereof. A fourth cost function may include risk related terms such as safety cost, drilling difficulty, productivity loss, or a combination thereof. A fifth cost function may include terminal cost for target endpoint, which may help with solution stability when added to such optimization problems. [0041] A second example component that may be used when determining the optimal trajectory of the wellbore may include constraints. The constraint functions of wellbore target trajectory planning problem may be a combination of one or more of the following functions. A first example constraint function may include limits for specific terms, if provided by the user for any reason. This could be limits for any involved attributes such as depth (e.g., stratigraphic depth, true vertical depth, relative depth, etc.), angular (e.g., inclination, azimuth), spatial (e.g., easting, northing), shape of the trajectory (e.g., DLS, tortuosity, build rate, turn rate), drilling parameters (e.g., ROP, WOB), velocity (e.g., force, torque), etc., or a combination thereof. [0042] Such constraints may be posed as soft constraints or hard constraints. A soft constraint may be defined as a constraint such that violation will cause a penalty. A hard constraint may be defined as a constraint that must be satisfied. To illustrate, FIG.6 is a graph of example soft and hard constraints of a wellbore planning trajectory along a true vertical depth of a wellbore, according to some embodiments. FIG.6 depicts a graph 600 having an x-component 602 that includes the measured depth of the wellbore and a y-component 604 that includes the true vertical depth of the wellbore. [0043] The graph 600 also includes a plot 606 that is the original well plan for drilling the wellbore from approximately 5200 to 7200 feet (ft) and a location 610 where the drill bit is currently located (at approximately 5500 ft). The graph 600 also includes plots 612 and 614 which are both soft constraints. For example, the plot 612 may be rate of penetration (ROP), and the plot 614 may be weight on bit (WOB). The graph 600 also includes a plot 616 which is a hard constraint (such as a turn rate of the trajectory). The graph 600 is depicted in two dimensions. However, such constraints may often times be posed in three dimensions. [0044] As part of optimization of the trajectory, the cost may be minimized as shown in Equation (1) below: ^ m ౡ,i^n ౡ_{J^x୩, u୩^ ൌ J୮^x୩, u୩^ ^ J^^x୩, u୩^ (1)} [0045] wherein J(xk , uk) is a function of xk and uk that is an objective (cost) for position and smoothness. Thus, J(xk , uk) is Jp(xk, uk) (a function of position with regard to xk and uk^ plus J_s(x_k, u_k) (a function of smoothness with regard to x_k and u_k). _{[0046] For example, J୮^x୩, u୩^ ^ J^^x୩, u୩^ may be J(TVD-ref) + J(Azi-ref) + J(DLS} smoothness). Also, x and u may be defined by Equations (2) and (3) below, respectively: x = [TVD, inc, azi] (2) y = [Kinc, Kazi, DLS] (3) [0047] In some implementations, this minimization of cost may be subject to (a) the dynamics models, (b) constraints, and (c) planning horizon. For example, the dynamic models may be defined by Equation (4) below: x_{୩ା^ ൌ Ax୩ ^ Bu୩ (4)} [0048] x_k and u_k together are the solution (states) to the target planning problem. For example, xk may denote states related to location, altitude, etc., and uk denotes states related to steering controls such as torque, ROP, DLS, etc. An example of the dynamic model may be based on Equations (5) and (6): Kinc ^^inc (5) ^^^^^^^^^^azi (6) [0049] wherein change in true vertical depth to change in measured depth may be defined based on Equation (7): ^^{்^^} ^ெ^ _{ൌ cos^^^^^^^^ (7)} [0050] and wherein DLS (dog leg severity) may be defined based on Equation (8): D_{LSଶ ൌ Kincଶ ^ Kaziଶ*sin(inc) (8)} [0051] Examples of constraints (to which minimization of cost may be subject to) may be defined by Equations (9), (10), and (11) below: f_{^x୩^ ^ ν (9)} _{h^u୩^ ^ ρ (10)} _{g^x୩^ ൌ μ (11)} [0052] In some implementations, Equations (9)-(11) may be symbolic representations of all the constraints being considered and summarized, in which A, B, ν, ρ, μ are some coefficients, and f,h,g are some functions. For example, Equation (9) may be a boundary condition; Equation (10) may be terminal constraints; and Equation (11) may be an initial condition. [0053] The planning horizon (to which minimization of cost may be subject to) may be defined by Equation (12): k_{ൌ 0,1, … , N୮ (12)} [0054] The planning horizon includes a discrete sampling rate based on k. Thus, the dynamic models, the constraints and the planning horizon may be valid over each value of k (from 0 to Np). [0055] In some implementations, these operations may be applicable to different types of wellbores (such as vertical, landing, lateral, etc.). Additionally, in some implementations, what is considered success criteria with regard to optimization of the trajectory may vary. For example, a success criteria may be that the path of the wellbore should be within a reservoir. Another example of a success criteria may be that the path of the wellbore be within a defined range of a specified boundary. For instance, the success criteria may be that a distance of the path of the wellbore remains within a defined distance (such as 1 foot, 5 feet, 10 feet, etc.) of the upper boundary of the target zone (versus the lower boundary of the target zone). Another example of a success criteria may be that the path of the wellbore stays within a zone within a reservoir. Such defined success criteria may, therefore, affect the different variables (such as the constraints) that define the optimization of the trajectory of the wellbore. [0056] A second example constraint function may include an additional limit for specific terms over certain measured depth. This could be, for example, to avoid collision with obstacles (such as previously drilled wells, drilling hazards, hard formations like rocks), to maintain certain distance from bed boundaries or water-oil-contact; etc., or a combination thereof. [0057] A third example constraint function may be constraints due to knowledge of tool dynamics and wellbore dynamics based on tool settings and neighboring subterranean condition. These may be defined as constraints (such as kinematics constraints (e.g., dogleg severity), safety constraints, velocity constraints (e.g., force, torque), drag constraints that maximize ROP of a drill bit, etc. In some implementations, one or more constraints may be relaxed locally (use techniques such as barrier functions, slack variables, etc.) to ensure feasibility of the optimization. [0058] A third example component that may be used when determining the optimal trajectory of the wellbore may include one or more initial conditions. Examples of such initial conditions may include the current location of the drill bit, the current location of the wellbore. These initial conditions may be extracted from the wellpath and may depend on the availability and/or uncertainty of the measurements. In some implementations, the constraints may be relaxed accordingly (use techniques such as barrier functions, slack variables, etc.) based on the initial condition, to ensure feasibility of the optimization. In some implementations, such optimization may be assumed to have recursive feasibility. [0059] A third example component that may be used when determining the optimal trajectory of the wellbore may include the sampling rate. The sampling rate of the discrete planned wellbore trajectory may be either specified by the user or determined based on trade-offs between computed lower and upper bound. In some implementations, the sampling rate need not to be a constant. Rather, the sampling rate may vary with respect to the planning horizon. [0060] In some implementations, the lower bound may consider (1) providing adequate response time for drilling and anti-collision, given different steering capacities and (2) a rate that is a multiple of the control algorithm frequency to minimize jitter. In some implementations, the upper bound may consider (1) Nyquist frequency of the sensor measurements, (2) ensuring that noise does not dominate the input signal, and (3) conserve processor time, especially when the planning horizon gets large. [0061] A fourth example component that may be used when determining the optimal trajectory of the wellbore may include the planning horizon. The planning horizon may be defined based on the total depth that the wellbore is expected to reach within the hydrocarbon reservoir. [0062] Returning to operations of the flowchart 500 of FIG.5, operations continue at block 512. [0063] At block 512, steering of the drilling of the wellbore is controlled based on the optimized trajectory. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may perform this operation. In some implementations, the processor 201 may perform this operation by using at least one controller at the surface (at or near the wellbore 116 or remote from the wellbore 116) and/or downhole in the wellbore 116. For example, different level of controllers (such as a model predictive control (MPC) controller, a proportional-integral- derivative (PID) controller, etc.) through varying relevant control actions in order to follow the planned target trajectory. Operations of the flowchart 500 continue at block 514. [0064] At block 514, a determination is made of whether a total depth of the wellbore has been drilled. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may make this determination. The value of total depth of the wellbore may be set to any value and may be set as part of the initial plan for the wellbore or may change during the drilling of the wellbore. If the total depth of the wellbore has been reached, operations of the flowchart 500 are complete. Otherwise, operations of the flowchart 500 continue at blocks 516 and 518. [0065] At block 516, the geoscience model is updated. For example, with reference to FIGS. 1-2, the processor 201 of the computer 200 may perform this updating. In some implementations, the processor 201 may update the geoscience model based on the latest geosteering interpretations, planned target trajectory and control decisions. For example, sensors that are part of the bottomhole assembly 124 of the drill string 108 may detect any changes in the geology, geophysical data, the geo-mechanical data. The processor 201 may receive these changes from the sensors downhole. Also, sensors at the surface and/or downhole may provide data regarding the geosteering of the wellbore. The processor 201 may receive this data to update the geoscience model based on such data. Operations of the flowchart 500 return to block 502 to retrieve the geoscience data (as described above). [0066] At block 518, the drilling operation data is updated. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may perform this updating. In some implementations, the processor 201 may update the drilling operation data based on the latest geosteering interpretations, planned target trajectory and control decisions. The processor 201 may receive these changes from the sensors downhole. Also, sensors at the surface and/or downhole may provide data regarding the geosteering of the wellbore. The processor 201 may receive this data to update the drilling operation based on such data. Operations of the flowchart 500 return to block 504 to retrieve the drilling operation (as described above). Accordingly, operations of the flowchart 500 may continue until a total depth of the wellbore has been reached. [0067] FIG.7 is a block diagram of a second example flowchart for wellbore target trajectory planning and geosteering for drilling a wellbore, according to some embodiments. Operations of a flowchart 700 of FIG.7 are described with reference to FIGS.1-2. Operations of the flowchart 700 start at block 702 and block 704. [0068] At block 702, geoscience data for the subsurface formation through which the wellbore is being drilled is retrieved. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may retrieve the geoscience data for the subsurface formation through which the wellbore 116 is being drilled. Similar to operations at block 502 of the flowchart 500 of FIG.5, the processor 201 may retrieve the geoscience data from various available sources (such as databases stored in machine-readable media, sensors that are positioned downhole in the wellbore 116, etc. This geoscience data may include (a) geophysical data such as seismic data; (b) geological data such as petrophysical data and facies classification; (c) geo-mechanical data such as pressure data, stress data; etc. Overall, the geoscience data may provide insight to the location of geological discontinuities, such as faults, and sedimentary layers as well as to the physical properties of rock such as type, porosity, and thickness of each sedimentary layer. Operations of the flowchart 700 continue at block 704. [0069] At block 704, the geoscience data for the subsurface formation through which the wellbore is being drilled is processed. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may process this retrieved geoscience data. Similar to operations at block 504 of the flowchart 500 of FIG.5, processing this data may include summarizing subterranean formation, location that the wellbore should stay within or away from, etc. As part of processing of this geoscience data, factors that may be considered may include: (1) certain bed boundaries based on user’s specification, (2) avoidance of collision with obstacles such as previously drilled wells, drilling hazards, hard formations like rocks, etc. (3) maintaining certain distance from bed boundaries or water-oil-contact, and (4) staying at certain zones that maximize productivity within a hydrocarbon reservoir. Operations of the flowchart 700 continue at block 709. [0070] At block 706, drilling operation data for the wellbore being drilled is retrieved. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may retrieve the drilling operation data for drilling the wellbore 116. Similar to operations at block 507 of the flowchart 500 of FIG.5, the processor 201 may retrieve the drilling operation data from various available sources (such as databases stored in machine-readable media, sensors that are positioned downhole in the wellbore 117, etc. For example, the processor 201 may retrieve historical drilling operation data from a previously drilled section of the current wellbore or from offset wells. Historical drilling data may include a wellbore path (that includes location, altitude, etc.), drill bit and hole information, dogleg severities, tool dynamics and wellbore dynamics, dynamic and/or static drilling parameters, etc. Historical drilling data may provide insight into how the wellbore path could possibly be drilled and basic operational limits while drilling a wellbore trajectory. Operations of the flowchart 700 continue at block 708. [0071] At block 708, the drilling operation data for the wellbore being drilled is processed. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may process the drilling operation data. Similar to operations at block 508 of the flowchart 500 of FIG.5, processing this data may include summarizing operational parameter settings and limits. Factors that may be considered when processing the drilling operation data may include current location of the drill bit and hole location and wellpath, which should provide knowledge of the starting condition of the planned wellbore. Other factors may include knowledge of current tool dynamics and borehole dynamics based on tool settings and neighboring subterranean conditions. These factors may subsequently be used to define constraints such as kinematics constraints (e.g., dogleg severity), safety constraints, or velocity constraints (e.g., force, torque), or drag constraints that maximize ROP of a drill bit. Another factor that may be considered when processing the drilling operation data may include total depth that the wellbore is expected to reach within the hydrocarbon reservoir. Operations of the flowchart 700 continue at block 709. [0072] At block 709, a determination is made of whether a trajectory trigger event has occurred. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may make this determination. For instance, the processor 201 may determine whether the trajectory trigger event has occurred since the last time this determination was made. [0073] The trigger may automatically determine whether an updated wellbore target trajectory is needed. The trigger may be a single logic or based on a combination of several criteria. An example of such criteria may be a time-based trigger, wherein the trigger is to occur after certain interval of time. For example, the trigger may be 30 minutes. In this example, the trajectory event may be considered to have occurred if 30 minutes had elapsed since the last time the trajectory was optimized. If this is the initial check since the start of these operations, the trajectory event may be considered to have occurred if 30 minutes had elapsed since the start of these operations. [0074] Another example of such criteria for the trigger may be a depth-based trigger, wherein the trigger is to occur after certain interval of depth. For example, the trigger may be 200 feet. In this example, the trajectory event may be considered to have occurred if the wellbore had been drilled an additional 200 feet since the last time the trajectory was optimized. If this is the initial check since the start of these operations, the trajectory event may be considered to have occurred if the depth of the wellbore is at least 200 feet since the start of these operations. [0075] Another example of such criteria for the trigger may be based on changes in the geoscience model. For example, the trigger may be that at least one attribute of the geoscience model has changed beyond a threshold. Examples of such attributes may include attributes related to geophysical data (such as seismic data), geological data (such as petrophysical data and facies classification) or geo-mechanical data (such as pressure data or stress data). Accordingly, if a value of at least one attribute of the geoscience model changes beyond a threshold, the trigger event has occurred. For instance, if the pressure of the subsurface formation exceeds a “change in pressure trigger” threshold and seismic waves traversing through the subsurface formation exceeds a “change in seismic waves trigger” threshold, the trigger event is considered to have occurred. [0076] To illustrate, FIG.8 is a graph of an example of when at least one attribute of the geoscience model has gained sufficient changes to trigger an event, according to some embodiments. FIG.8 depicts a graph 800 having an x-component 802 that includes the depth of the drill bit and a y-component 804 that includes a delta true vertical depth. The delta that may trigger the event for at least one attribute of the geoscience model may be defined by a lower limit 810 where the value of the delta true vertical depth is -50 and an upper limit 812 where the value of the delta true vertical depth is 50. Accordingly, if the value of the at least one attribute of the geoscience model that is being used to determine whether a trigger event has occurred is below the lower limit 810 or above the upper limit 812 (since the last time it was determined whether a trigger event has occurred), then a trigger event is considered to have occurred. [0077] Another example of such criteria for the trigger may be based on at least one scoring mechanism. For example, the trigger may be that a defined scoring metric has fallen below a defined threshold. Examples may include a parameter confidence score, geoscience model quality score, bit location uncertainty score, etc. For example, the scores may range from 70-100, wherein the defined threshold may be 91. If one or more of these scores fall below the defined threshold, the trigger event may be considered to have occurred. [0078] To illustrate, FIG.9 is a graph of an example of when a scoring mechanism is to trigger an event, according to some embodiments. FIG.9 depicts a graph 900 having an x- component 902 that includes the depth of the drill bit and a y-component 904 that includes a score. The graph 900 also includes a threshold 910 at a scoring value of 92. Accordingly, the trigger event may occur when the defined scoring metric falls below the threshold 910. Examples of the scoring metric may be at least one of a parameter confidence score, geoscience model quality score, bit location uncertainty score, etc.). [0079] Returning to the operations of the flowchart 700 of FIG.7, if the trajectory trigger event has not occurred, operations continue at blocks 716 and 718 (further described below). If the trajectory trigger event has occurred, operations of the flowchart 700 continue at block 710. [0080] At block 710, a trajectory of well path is optimized based on the processed geoscience data and the processed drilling operation data. For example, with reference to FIGS. 1-2, the processor 201 of the computer 200 may perform this operation. Similar to operations at block 510 of the flowchart 500 of FIG.5, the processor 201 may formulate a trajectory optimization problem based on the processed geoscience data and the processed drilling operation data. The formulated problem may be solved for a target trajectory over the planning horizon. In some implementations, the solution may contain any (independent) state required for steering controls and operations. As described above, different components may be used for optimization of the trajectory. These components may include: 1) cost function, 2) constraints, 3) initial condition, 4) sampling rate, and 5) planning horizon. Operations of the flowchart 700 continue at block 712. [0081] At block 712, steering of the drilling of the wellbore is controlled based on the optimized trajectory. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may perform this operation. Similar to operations at block 512 of the flowchart 500 of FIG.5, the processor 201 may perform this operation by using at least one controller at the surface (at or near the wellbore 116 or remote from the wellbore 116) and/or downhole in the wellbore 116. For example, different level of controllers (such as a model predictive control (MPC) controller, a proportional-integral-derivative (PID) controller, etc.) through varying relevant control actions in order to follow the planned target trajectory. Operations of the flowchart 700 continue at block 714. [0082] At block 714, a determination is made of whether a total depth of the wellbore has been drilled. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may make this determination. Similar to operations at block 514 of the flowchart 500 of FIG.5, the value of total depth of the wellbore may be set to any value and may be set as part of the initial plan for the wellbore or may change during the drilling of the wellbore. If the total depth of the wellbore has been reached, operations of the flowchart 700 are complete. Otherwise, operations of the flowchart 700 continue at blocks 716 and 718. [0083] At block 716, the geoscience model is updated. For example, with reference to FIGS. 1-2, the processor 201 of the computer 200 may perform this updating. Similar to operations at block 516 of the flowchart 500 of FIG.5, the processor 201 may update the geoscience model based the latest geosteering interpretations, planned target trajectory and control decisions. For example, sensors that are part of the bottomhole assembly 124 of the drill string 108 may detect any changes in the geology, geophysical data, the geo-mechanical data. The processor 201 may receive these changes from the sensors downhole. Also, sensors at the surface and/or downhole may provide data regarding the geosteering of the wellbore. The processor 201 may receive this data to update the geoscience model based on such data. Operations of the flowchart 700 return to block 702 to retrieve the geoscience data (as described above). [0084] At block 718, the drilling operation data is updated. For example, with reference to FIGS.1-2, the processor 201 of the computer 200 may perform this updating. Similar to operations at block 518 of the flowchart 500 of FIG.5, the processor 201 may update the drilling operation data based on the latest geosteering interpretations, planned target trajectory and control decisions. The processor 201 may receive these changes from the sensors downhole. Also, sensors at the surface and/or downhole may provide data regarding the geosteering of the wellbore. The processor 201 may receive this data to update the drilling operation based on such data. Operations of the flowchart 700 return to block 704 to retrieve the drilling operation (as described above). Accordingly, operations of the flowchart 700 may continue until a total depth of the wellbore has been reached. [0085] Operations described above (in reference to FIG.5 and/or FIG.7) may include different variations. For example, in some implementations, the operations may include formulations that may be used in either deterministic or stochastic fashion. When used with stochasticity, uncertainties may occur in the earth model, geosteering interpretation, location measurements of the wellpath, the drill bit, and/or the wellbore, steering operations, tool dynamics, wellbore dynamics, dynamic and/or static drilling parameters, etc., could be considered. [0086] Additionally, example implementations may operate over vertical, landing or horizontal sections, with minor modifications. In some implementations, when applied in a recursive or sliding-window fashion, operations may adapt changes in factors such as subterranean condition, drilling operation, etc. in real-time. For example, operations may utilize geoscience information and drilling operation information and automatically plan an optimal wellbore trajectory in response to the latest changes therein. [0087] In some implementations, when applied in a recursive or sliding-window fashion, operations may learn changes and trends in geoscience information and drilling operation information and build models based upon. In some implementations, operations may include a formulation that may be convexified, using techniques such as convex relaxation, convex envelop, etc. Such implementations may drastically improve computational performance, especially when dealing with large scale problems. [0088] While the aspects of the disclosure are described with reference to various implementations and exploitations, it will be understood that these aspects are illustrative and that the scope of the claims is not limited to them. Many variations, modifications, additions, and improvements are possible. [0089] Plural instances may be provided for components, operations or structures described herein as a single instance. Finally, boundaries between various components, operations and data stores are somewhat arbitrary, and particular operations are illustrated in the context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within the scope of the disclosure. In general, structures and functionality presented as separate components in the example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements may fall within the scope of the disclosure. Example Embodiments [0090] Example embodiments are now described. [0091] Embodiment #1: A method comprising: retrieving geoscience data of a subsurface formation into which a wellbore is being drilled; retrieving drilling operation data for drilling the wellbore; determining at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data; and modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations. [0092] Embodiment #2: The method of Embodiment #1, further comprising identifying at least one avoidance location in the subsurface formation through which the path of the wellbore should not include. [0093] Embodiment #3: The method of Embodiment #2, further comprising identifying operational parameter data that comprises at least one of operational parameter settings or operational parameter limits based on the drilling operation data. [0094] Embodiment #4: The method of Embodiment #3, wherein determining the optimized target trajectory of the path of the wellbore to be drilled comprises determining the optimized target trajectory based on the at least one avoidance location and the operational parameter data. [0095] Embodiment #5: The method of any one of Embodiments #1-4, further comprising: after retrieving the geoscience data and the drilling operation data, determining whether a trigger event has occurred; and after determining that the trigger event has occurred, determining the at least one of the optimized target trajectory of the path of the wellbore to be drilled or the series of control operations and modifying geosteering of the drilling of the wellbore. [0096] Embodiment #6: The method of Embodiment #5, wherein the trigger event comprises a time-based trigger that occurs after a defined interval of time. [0097] Embodiment #7: The method of Embodiment #5, wherein the trigger event comprises a depth-based trigger that occurs after a defined level of depth of drilling of the wellbore. [0098] Embodiment #8: The method of Embodiment #5, wherein the trigger event comprises a geoscience-based trigger that occurs in response to a threshold change in a geological attribute in the subsurface formation through which the wellbore is being drilled. [0099] Embodiment #9: The method of Embodiment #8, wherein the geological attribute comprises at least one of a porosity, a resistivity, or a percentage of water. [00100] Embodiment #10: A system comprising: a drill string comprising a drill bit to drill a wellbore in a subsurface formation; a processor; and a machine-readable medium having instructions stored thereon that are executable by the processor to cause the processor to, retrieve geoscience data of the subsurface formation into which the wellbore is being drilled; retrieve drilling operation data for drilling the wellbore; determine at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data; and modify geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations. [00101] Embodiment #11: The system of Embodiment #10, wherein the drill string comprises at least one sensor to detect geoscience data of the subsurface formation during drilling of the wellbore, and wherein the instructions to cause the processor to retrieve the geoscience data comprises instructions to cause the processor to retrieve the geoscience data detected by the at least one sensor. [00102] Embodiment #12: The system of any one of Embodiments #10-11, wherein the instructions comprise instructions that are executable by the processor to cause the processor to identify at least one avoidance location in the subsurface formation through which the path of the wellbore should not include, and identify operational parameter data that comprises at least one of operational parameter settings or operational parameter limits based on the drilling operation data, and wherein the instructions to cause the processor to determine the optimized target trajectory of the path of the wellbore to be drilled comprises instructions to cause the processor to determine the optimized target trajectory based on the at least one avoidance location and the operational parameter data. [00103] Embodiment #13: The system of any one of Embodiments #10-12, wherein the instructions comprise instructions to cause the processor to: after retrieving the geoscience data and the drilling operation data, determine whether a trigger event has occurred; and after determining that the trigger event has occurred, determine the at least one the optimized target trajectory of the path of the wellbore to be drilled or the control operations and modify geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations. [00104] Embodiment #14: The system of Embodiment #13, wherein the trigger event comprises a time-based trigger that occurs after a defined interval of time. [00105] Embodiment #15: The system of Embodiment #13, wherein the trigger event comprises a depth-based trigger that occurs after a defined level of depth of drilling of the wellbore. [00106] Embodiment #16: The system of Embodiment #13, wherein the trigger event comprises a geoscience-based trigger that occurs in response to a threshold change in a geological attribute in the subsurface formation through which the wellbore is being drilled. [00107] Embodiment #17: The system of Embodiment #16, wherein the geological attribute comprises at least one of a porosity, a resistivity, or a percentage of water. [00108] Embodiment #18: A non-transitory, computer-readable medium having instructions stored thereon that are executable by a processor to perform operations comprising: retrieving geoscience data of a subsurface formation into which a wellbore is being drilled; retrieving drilling operation data for drilling the wellbore; determining at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data; and modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of control operations. [00109] Embodiment #19: The non-transitory, computer-readable medium of Embodiment #18, wherein the operations comprise, identifying at least one avoidance location in the subsurface formation through which the path of the wellbore should not include; and identifying operational parameter data that comprises at least one of operational parameter settings or operational parameter limits based on the drilling operation data, and wherein determining the optimized target trajectory of the path of the wellbore to be drilled comprises determining the optimized target trajectory based on the at least one avoidance location and the operational parameter data. [00110] Embodiment #20: The non-transitory, computer-readable medium of Embodiment #19, wherein the operations comprise, after retrieving the geoscience data and the drilling operation data, determining whether a trigger event has occurred; and after determining that the trigger event has occurred, determining the at least one of the optimized target trajectory of the path of the wellbore to be drilled or the series of control operations, and modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of control operations. [00111] Embodiment #21: The non-transitory, computer-readable medium of Embodiment #20, wherein the trigger event comprises a time-based trigger that occurs after a defined interval of time. [00112] Embodiment #22: The non-transitory, computer-readable medium of Embodiment #20, wherein the trigger event comprises a depth-based trigger that occurs after a defined level of depth of drilling of the wellbore. [00113] Embodiment #23: The non-transitory, computer-readable medium of Embodiment #20, wherein the trigger event comprises a geoscience-based trigger that occurs in response to a threshold change in a geological attribute in the subsurface formation through which the wellbore is being drilled. [00114] Embodiment #24: The non-transitory, computer-readable medium of Embodiment #23, wherein the geological attribute comprises at least one of a porosity, a resistivity, or a percentage of water.

Claims

CLAIMS 1. A method comprising: retrieving geoscience data of a subsurface formation into which a wellbore is being drilled; retrieving drilling operation data for drilling the wellbore; determining at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data; and modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations.

2. The method of claim 1, further comprising identifying at least one avoidance location in the subsurface formation through which the path of the wellbore should not include.

3. The method of claim 2, further comprising identifying operational parameter data that comprises at least one of operational parameter settings or operational parameter limits based on the drilling operation data.

4. The method of claim 3, wherein determining the optimized target trajectory of the path of the wellbore to be drilled comprises determining the optimized target trajectory based on the at least one avoidance location and the operational parameter data.

5. The method of claim 1, further comprising: after retrieving the geoscience data and the drilling operation data, determining whether a trigger event has occurred; and after determining that the trigger event has occurred, determining the at least one of the optimized target trajectory of the path of the wellbore to be drilled or the series of control operations and modifying geosteering of the drilling of the wellbore.

6. The method of claim 5, wherein the trigger event comprises a time-based trigger that occurs after a defined interval of time.

7. The method of claim 5, wherein the trigger event comprises a depth-based trigger that occurs after a defined level of depth of drilling of the wellbore.

8. The method of claim 5, wherein the trigger event comprises a geoscience-based trigger that occurs in response to a threshold change in a geological attribute in the subsurface formation through which the wellbore is being drilled.

9. The method of claim 8, wherein the geological attribute comprises at least one of a porosity, a resistivity, or a percentage of water.

10. A system comprising: a drill string comprising a drill bit to drill a wellbore in a subsurface formation; a processor; and a machine-readable medium having instructions stored thereon that are executable by the processor to cause the processor to, retrieve geoscience data of the subsurface formation into which the wellbore is being drilled; retrieve drilling operation data for drilling the wellbore; determine at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data; and modify geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations.

11. The system of claim 10, wherein the drill string comprises at least one sensor to detect geoscience data of the subsurface formation during drilling of the wellbore, and wherein the instructions to cause the processor to retrieve the geoscience data comprises instructions to cause the processor to retrieve the geoscience data detected by the at least one sensor.

12. The system of claim 10, wherein the instructions comprise instructions that are executable by the processor to cause the processor to identify at least one avoidance location in the subsurface formation through which the path of the wellbore should not include, and identify operational parameter data that comprises at least one of operational parameter settings or operational parameter limits based on the drilling operation data, and wherein the instructions to cause the processor to determine the optimized target trajectory of the path of the wellbore to be drilled comprises instructions to cause the processor to determine the optimized target trajectory based on the at least one avoidance location and the operational parameter data.

13. The system of claim 10, wherein the instructions comprise instructions to cause the processor to: after retrieving the geoscience data and the drilling operation data, determine whether a trigger event has occurred; and after determining that the trigger event has occurred, determine the at least one the optimized target trajectory of the path of the wellbore to be drilled or the control operations and modify geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of the control operations.

14. The system of claim 13, wherein the trigger event comprises a time-based trigger that occurs after a defined interval of time.

15. The system of claim 13, wherein the trigger event comprises a depth-based trigger that occurs after a defined level of depth of drilling of the wellbore.

16. The system of claim 13, wherein the trigger event comprises a geoscience-based trigger that occurs in response to a threshold change in a geological attribute in the subsurface formation through which the wellbore is being drilled.

17. The system of claim 16, wherein the geological attribute comprises at least one of a porosity, a resistivity, or a percentage of water.

18. A non-transitory, computer-readable medium having instructions stored thereon that are executable by a processor to perform operations comprising: retrieving geoscience data of a subsurface formation into which a wellbore is being drilled; retrieving drilling operation data for drilling the wellbore; determining at least one of an optimized target trajectory of a path of the wellbore to be drilled or a series of control operations for the drilling in order to follow the path of the wellbore to be drilled, independent of using waypoints as input and based the geoscience data and the drilling operation data; and modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of control operations.

19. The non-transitory, computer-readable medium of claim 18, wherein the operations comprise, identifying at least one avoidance location in the subsurface formation through which the path of the wellbore should not include; and identifying operational parameter data that comprises at least one of operational parameter settings or operational parameter limits based on the drilling operation data, and wherein determining the optimized target trajectory of the path of the wellbore to be drilled comprises determining the optimized target trajectory based on the at least one avoidance location and the operational parameter data.

20. The non-transitory, computer-readable medium of claim 19, wherein the operations comprise, after retrieving the geoscience data and the drilling operation data, determining whether a trigger event has occurred; and after determining that the trigger event has occurred, determining the at least one of the optimized target trajectory of the path of the wellbore to be drilled or the series of control operations, and modifying geosteering of the drilling of the wellbore based on the at least one of the optimized target trajectory or the series of control operations.

21. The non-transitory, computer-readable medium of claim 20, wherein the trigger event comprises a time-based trigger that occurs after a defined interval of time.

22. The non-transitory, computer-readable medium of claim 20, wherein the trigger event comprises a depth-based trigger that occurs after a defined level of depth of drilling of the wellbore.

23. The non-transitory, computer-readable medium of claim 20, wherein the trigger event comprises a geoscience-based trigger that occurs in response to a threshold change in a geological attribute in the subsurface formation through which the wellbore is being drilled.

24. The non-transitory, computer-readable medium of claim 23, wherein the geological attribute comprises at least one of a porosity, a resistivity, or a percentage of water.