Abstract: Embodiments are directed to methods, systems and user interfaces for assessing reservoir management competency for a petroleum producing field. In one scenario, a computer system measures, using various hardware-based sensors positioned in a petroleum reservoir supplying the petroleum producing field, physical or geological characteristics of the petroleum reservoir. The computer system establishes a reservoir management competency scoring system that evaluates a specific set of objective criteria that reflect a level of reservoir management competency at the petroleum producing field, and automatically generates, according to the objective set of criteria of the reservoir management competency scoring system, a reservoir management rating for the petroleum reservoir based at least in part on data measured by the sensors placed in the petroleum reservoir.

Abstract: Embodiments are directed to managing and improving a drilling and completions process at a hydrocarbon extraction site, and to optimizing resource allocation at a hydrocarbon extraction site/region. In one scenario, a computer system accesses data generated by hardware sensors implemented by drilling and completion equipment at a hydrocarbon extraction site. The computer system formats the sensor data into a form readable by a data mining algorithm, and mines the formatted sensor data to identify characteristics related to the drilling and completion process. The computer system also accesses and integrates historical data related to the drilling and completion equipment at the hydrocarbon extraction site. The computer system then computes drilling and completion performance indicators that identify inefficiencies based on the characteristics identified for the equipment and based on the accessed historical data. Then, a remediation step is performed to resolve the identified inefficiency.

Abstract: A method of improving operation of a petroleum reservoir using geotechnical and economic analysis includes classifying a petroleum reservoir using reserves ranking analytics (RRA) and then making one or modifications to the operation of the reservoir. RRA classification includes establishing reservoir classification metrics for each of the following categories: 1) resource size; 2) recovery potential; and 3) profitability. The reservoir can be classified based on at least one metric in the profitability classification category, and also based on at least one metric in one or more of the resource size classification category or the recovery potential classification category. Classification of reservoirs according to RRA can aid in reservoir management, planning, and development.

Abstract: Methods and systems for increasing the recovery efficiency of a petroleum reservoir. For example, a method for performing a petroleum recovery assessment to increase the recovery efficiency of a petroleum reservoir includes evaluating results associated with a reservoir management analysis for the petroleum reservoir and generating a reservoir management analysis score. The method further includes evaluating results associated with a global benchmark analysis and generating an estimated maximum recovery efficiency for the petroleum reservoir. The method further includes determining key recovery obstacles impeding the petroleum reservoir from achieving the estimated maximum recovery efficiency, and identifying field development opportunities addressing a key recovery obstacle that when implemented, increases a recovery efficiency for the petroleum reservoir closer to the estimated maximum recovery efficiency.

Abstract: Embodiments are directed to automatically detecting an event in a production curve, generating a production estimate using a quantile regression and to performing a probabilistic decline curve analysis. In one scenario, a computer system identifies a candidate break point in a production decline curve which represents a decline in material production at a well. The computer system identifies one trend for the production decline curve occurring before the candidate break point and identifies a second trend for the production decline curve occurring after the candidate break point. The computer system calculates the difference between the first material production decline estimate and the second material production decline estimate and identifies the candidate break points where the difference between the first material production decline estimate and the second material production decline estimate is beyond a threshold value.

Abstract: Embodiments are directed to modeling physical material flow relationships between injector wells and producer wells in a reservoir and to quantifying a level of uncertainty in a connection-based model. In one scenario, a computer system calculates pressure distribution within the reservoir using sensor data. Next, the computer system applies the calculated pressure distribution as an input to a tracer algorithm for an injector well and for a producer well to identify tracer flow values for materials flowing from the injector well to the producer well. The computer system further combines the identified tracer flow values to generate well allocation factors representing relationships in material flow.

Abstract: Determining a Reservoir Management Factor™ (RMF™ or ?) for a petroleum producer provides a novel metric, selection, design, implementation and monitoring tool designed for use in implementing capital projects for increasing production and reserves of the petroleum producer. The RMF or ? can be determined according to the following equation: ?=sum of regression coefficients=sum of (reserves coefficient, production coefficient) wherein, reserves coefficient=the coefficient of the petroleum producer's reserves; and production coefficient=the coefficient of the petroleum producer's production. The producer can based on the RMF, select, design, implement and monitor one or more capital projects for increasing production and reserves of the petroleum producer. The capital projects can include drilling additional wells, stimulating existing wells, and increasing reservoir contact of existing wells.

Abstract: A method of improving operation of a petroleum reservoir using geotechnical analysis includes classifying a petroleum reservoir using a Reservoir Ranking Analysis (RRA) and then making one or modifications to the operation of the reservoir. RRA classification includes establishing reservoir classification metrics for at least resource size and recovery potential, and optionally profitability. The reservoir can be classified based on at least one metric in the profitability classification category, and also based on at least one metric in one or more of the resource size classification category or the recovery potential classification category. Classification of reservoirs can aid in reservoir management, planning, and development.

Abstract: Embodiments are directed to performing material balance analysis for tanks in a petroleum reservoir and to performing dual porosity material balance analysis. In one scenario, a computer system divides a reservoir into multiple tank blocks, where at least two tank blocks are adjacent. The adjacent tanks are connected at a tank block boundary so that materials are permitted to travel between the tank blocks. The computer system determines flow rate between adjacent tank blocks proportional to the difference in tank block pressures. Then, upon making this determination, the computer system determines material balance for at least some of the tank blocks in the reservoir through influx and efflux of material across the tank block boundary. The material balance includes a determined material balance for one of the adjacent tank blocks and a determined material balance for the other adjacent tank block.

Abstract: Determining a True Value Index™ (TVI™) for a petroleum production capital project provides a novel indicator and metric that is designed to quickly assess the economics of undertaking the petroleum production capital project. The TVI™ can be determined according to the following equation: TVI=NPV+(?*Reserves) where, NPV=Net present value of a project; ?=Reservoir Management Factor (RMF™)=absolute value (sum of Coefficient of Reserves and Coefficient of Production) derived from multivariable correlation=to reflect the market value premium on increased reserves if the producer was public; and Reserves=Barrels of proven reserves to be created by the project.

Abstract: Performing a Recovery Design Assessment™ (RDA™) for a petroleum producing field provides a novel indicator and metric that is designed to assess how to improve recovery efficiency of a petroleum producing field. A combination of global benchmark analysis and reservoir management assessment is utilized to identify areas of reservoir management that can be improved to increase recovery efficiency. Global benchmark analysis can include comparing a recovery efficiency for a petroleum reservoir to that of other benchmark petroleum reservoirs to indicate if alterations to recovery design or developments plans or reservoir management optimizations are to be pursued. Management of the petroleum reservoir is assessed to identify recovery obstacles potentially reducing recovery efficiency. Development opportunities for overcoming recover obstacles can be implemented to increase recovery efficiency.

Abstract: Determining a production gain index (PGI) for a petroleum reservoir provides a novel leading indicator and metric that is designed to quickly assess the potential for increases in production of petroleum from an operating petroleum reservoir when implementing a recovery plan. The PGI can be determined according to the following equation: P ? ? G ? ? I = ?? ? ? q A ? ? ? q Old where, ??qA=net actual production gain of the reservoir; and ?qOld=sum of current oil rates for existing producers. The PGI can also be determined according to the following equation: PGI=PR×(GPI?1) where, GPI=the global productivity index of the petroleum reservoir; and PR=the interference factor, which accounts for any losses in aggregate production gain due to well interference.

Abstract: Determining a Recovery Deficiency Indicator™ (RDI™) for a petroleum reservoir provides a novel leading indicator and metric that is designed to quickly assess the potential for increases in reserves and ultimate recovery of petroleum from an operating petroleum reservoir. The RDI™ is determined by relating the Recovery Efficiency (RE) and the Ideal Recovery Efficiency (IRE) (e.g., by dividing RE by IRE to obtain RDI™). The Recovery Efficiency (RE) is determined as the product of areal displacement efficiency (EA), vertical displacement efficiency (EV), and pore displacement efficiency (ED). The Ideal Recovery Efficiency (RE) can be determined by empirically assuming that EA and EV equal 100%.

Abstract: Methods for accurately assessing the condition of a petroleum reservoir and designing and implementing a plan of action to increase production and recovery of petroleum from the reservoir. Information is gathered using a unique set of metrics and information gathering techniques and analyzed in a targeted fashion by properly weighting the data in the context of the particular reservoir and goals of the producer. A reservoir rating is generated using asymmetric analysis of metrics and then used to formulate a plan of action. Production architecture (e.g., number, location and manner of constructing oil and injector wells) is then constructed according to the plan of action. Reservoir performance can be continuously monitored and used to verify production and recovery goals and/or provide triggers or alarms to alter production equipment.

Abstract: Methods for accurately assessing the condition of a petroleum reservoir and designing and implementing a plan of action to increase production and recovery of petroleum from the reservoir. Information is gathered using a unique set of metrics and information gathering techniques and analyzed in a targeted fashion by properly weighting the data in the context of the particular reservoir and goals of the producer. A reservoir rating is generated using asymmetric analysis of metrics and then used to formulate a plan of action. Production architecture (e.g., number, location and manner of constructing oil and injector wells) is then constructed according to the plan of action. Reservoir performance can be continuously monitored and used to verify production and recovery goals and/or provide triggers or alarms to alter production equipment.