Various embodiments include apparatus and methods implemented to monitor detection of a flood front of a waterflood in a formation. Embodiments can include control of current in a set of three current electrodes to inject current into a formation around a pipe in a wellbore, where the three current electrodes include two of the electrodes to inject current and the third electrode to operatively provide a current return. Response of the formation to the current injections can be communicated by interrogating an optical fiber that extends along a longitudinal axis of the pipe. Determination of progression of the waterflood with respect to the wellbore can be provided from controlling the current and interrogating the optical fiber over time. Additional apparatus, systems, and methods are disclosed.

In accordance with one embodiment, a method of locating mineral deposits suitable for production comprises obtaining via a computer an image of an area of land, determining from the image at least one fluid-expulsion structure present on the land, designating an area proximate the fluid-expulsion structure as a mineral exploration location; while in accordance with another embodiment a method of locating a hydrocarbon reservoir suitable for production is described which comprises obtaining via a computer an image of an area of land, determining from the image at least one fluid-expulsion structure present on the land, and designating an area proximate the fluid-expulsion structure as a hydrocarbon exploration location.

In accordance with one embodiment, a method of locating mineral deposits suitable for production comprises obtaining via a computer an image of an area of land, determining from the image at least one fluid-expulsion structure present on the land, designating an area proximate the fluid-expulsion structure as a mineral exploration location; while in accordance with another embodiment a method of locating a hydrocarbon reservoir suitable for production is described which comprises obtaining via a computer an image of an area of land, determining from the image at least one fluid-expulsion structure present on the land, and designating an area proximate the fluid-expulsion structure as a hydrocarbon exploration location.

Systems and methods include a method for downhole leak detection and prediction in water injection wells. Bulk well operation information for one or more wells is accessed from a database. Real-time pressure and water rate information is received from surface and downhole gauges during operation of a water injection well. Engineered prediction-ready data is generated using the real-time pressure and water rate information by translating the bulk well operation information. Early signs of leakage at sub-surfaces of the water injection well are determined using the engineered prediction-ready data and wellbore dynamics of the water injection well. Information associated the early signs of leakage is provided based on the determining and for presentation to one or more users.

Systems and methods include a method for downhole leak detection and prediction in water injection wells. Bulk well operation information for one or more wells is accessed from a database. Real-time pressure and water rate information is received from surface and downhole gauges during operation of a water injection well. Engineered prediction-ready data is generated using the real-time pressure and water rate information by translating the bulk well operation information. Early signs of leakage at sub-surfaces of the water injection well are determined using the engineered prediction-ready data and wellbore dynamics of the water injection well. Information associated the early signs of leakage is provided based on the determining and for presentation to one or more users.

Systems and methods for intelligent estimation of productivity index and reservoir pressure values using pressure sensors, a neural network model comprising historical flow rate data of at least a well bore, and a data processor. The pressure sensors generate pressure data associated with a well bore's surface point and a downhole point. The data processor, communicatively coupled to the two pressure sensors and the neural network model, is operable to receive the pressure data from the sensors respectively indicative of pressure at each of the two points, estimate a real-time productivity index value in real-time based on the pressure data from the pressure sensors and the historical flowrate data of the neural network model, and estimate a reservoir pressure value of the well bore at a flowing condition, a reservoir pressure value of the well bore at a shut-in condition, or both, based on the real-time productivity index.

Systems and methods for intelligent estimation of productivity index and reservoir pressure values using pressure sensors, a neural network model comprising historical flow rate data of at least a well bore, and a data processor. The pressure sensors generate pressure data associated with a well bore's surface point and a downhole point. The data processor, communicatively coupled to the two pressure sensors and the neural network model, is operable to receive the pressure data from the sensors respectively indicative of pressure at each of the two points, estimate a real-time productivity index value in real-time based on the pressure data from the pressure sensors and the historical flowrate data of the neural network model, and estimate a reservoir pressure value of the well bore at a flowing condition, a reservoir pressure value of the well bore at a shut-in condition, or both, based on the real-time productivity index.

A numerical method for simulating a Karez well in association with a groundwater model includes: first, a Karez well section is divided into an underground channel, an open channel and an overflow area, wherein corresponding parameter values are assigned to each part; second, a Karez well conceptual model is established according to the parameters; third, based on the conceptual model, a dynamic relationship between the Karez well and groundwater is simulated using finite difference matrix equations; fourth, a water balance calculation is performed on the converged simulation result (head values); finally, water balance errors, parameter values in the conceptual model and the simulated head value are computed and output for all time periods. This method can simulate the whole process of the Karez well water flow from water collection to water impounding, providing a new approach for analyzing the Karez well seasonal water demand while used in agricultural water management.

Disclosed is a system and a method for monitoring water inrush, including: a host terminal, a field host, at least one controller and at least one electrode array. Each electrode array is placed in one borehole and to detect electric field signals of surrounding rocks around the borehole; each controller connects with one electrode array and is to control the electrode array to carry out a high-density induced polarization measurement on the surrounding rocks; the field host connects with the controller and is to send control signals to the controller, receive and process the electric field signals output by the electrode array; and the host terminal connects with the field host and is to receive the electric field signals processed by the field host, determine changes on apparent resistivity and apparent chargeability of the surrounding rocks, and determine whether there exists water inrush according to the changes.

A system for creating a 4D guided history matched model may include a network of saturation sensors and a model processing hub. The saturation sensors may identify water production rates. The model processing hub may be in communication with the network of saturation sensors and may include a reservoir simulation model and a processor. The processor of the model processing hub may build a 4D saturation model, compare the reservoir simulation model and the 4D saturation model to generate a saturation Δ, calculate updated permeability distribution data, and update the reservoir simulation model with the updated permeability distribution data to create the 4D guided history matched model. A method of creating a 4D guided history matched model may include comparing a reservoir simulation model and a 4D saturation model, calculating updated permeability distribution data, and updating the reservoir simulation model to create the 4D guided history matched model.