Page tree
Skip to end of metadata
Go to start of metadata


Specific type of Production Analysis (PA) workflow based on correlation between multi-well production/injection history and bottomhole pressure history from permanent downhole gauges (PDG).

The key simulation engine of MRT is Pressure Convolution which is based on Unit-rate Transient Responses (UTR) retrieved from Production rates / PDG data history by means of Pressure Deconvolution.

It does not require new data acquisition at well site and makes use of historical dynamic data records, usually few months or longer.


Motivation



Production rate in producing well depends on its productivity index J, current formation pressure p_e and current BHP p_{wf}:

(1) q_1^{\uparrow}(t)=J \cdot \left( p_e(t) - p_{wf}(t) \right)

and as such depends on completion/lift settings (defining p_{wf}(t)) and how formation pressure is maintained p_e = p_e(t) over time.

It keeps declining due to the offtakes:

(2) p_e(t) = p_e[q_1^{\uparrow}(t), q_2^{\uparrow}(t), q_3^{\uparrow}(t), \dots]

and maintained by either aquifer or Fluid Injection and in the latter case depends on injection rates:

(3) p_e(t) = p_e[q_1^{\downarrow}(t),q_2^{\downarrow}(t),q_3^{\downarrow}(t),\dots ]

The combination of (1)(2) and (3) lead to the correlation between production rates, injection rates and bottomhole pressure variation.


The ultimate purpose of MRT is to extract maximum information from correlation between the long-term (few months or longer) flowrate history and BHP history (recorded by PDG).

It is essentially based on the fact that BHP in a given well (whether producing or injecting) responds to flowrate variation in the same well and may (or may not) respond to flowrate variation in offset wells.

This information is further related to well flow performance and cross-well connectivity.


Goals & Objectives



  • Create short-term prediction model on production response to various multi-well production regimes

  • Compare the well dynamics and and cross-well connectivity with expectations and identify the candidates for drilling, workover or additional well surveillance

  • Assess dynamic reservoir properties


Outputs



Production History



Simulated total subsurface flowrate history, q_t(t)

Simulated BHP history, p_{wf}(t)

Simulated formation pressure history, p_e(t)

Simulated Productivity Index history, J_t(t)

Simulated Cross-well interference historyp_{k \rightarrow m}(t)

Production Forecast

Rate forecast under Pressure Control regime, p_k(t), \{ q_m(t) \} \rightarrow q_k(t)

BHP forecast under Liquid Control regime, \{ q_m(t) \} \rightarrow p_{wf, \, k}(t)

Formation pressure forecast under Liquid Control regime, \{ q_m(t) \} \rightarrow p_{e, \, k}(t)

Diagnostic Metrics









Cross-well interference map
Unit-rate Transient Response Matrix (UTRM)
Unit-rate Transient Response Spider (UTRS)
Material Balance Pressure Plot
Inflow Performance Relationship (IPR)
Cumulative Productivity Plot (Hall Plot)
J-plots
WOR diagnostics
GOR diagnostics
Primary Well & Reservoir properties


Potential drainage volume
Current dynamic drainage volume
Secondary Well & Reservoir properties




Apparent transmissibility
Apparent skin-factor 
Fracture half-length
Dynamic fracture pressure threshold


Inputs



Primary Inputs 



PVT model 
Production/injection history for all wells in a test
Bottom-hole pressure (BHP) history for at least one well
Additional Inputs









Well locations map
Well schematic
Surface Well Tests

Drilled formation pressurep_d from DST – Drill Stem Test

Drilled formation pressurep_d from WFT – Wireline Formation Test

Production Logging Reports
Cased-Hole Pressure Transient Test Reports
SGS – Static Gradient Survey Reports
Well Intervention History


Applications



Production forecasts


Predict formation pressure without shutting wells down and avoiding production deferment
Short-term production forecasts for different multi-well production scenarios
Selecting well-intervention candidates




Identify well-intervention candidates with possible thief production/injection
Identify well-intervention candidates with possibly inefficient reservoir flow profile
Identify well-intervention candidates for Rate Optimization
Identify well-intervention candidates for producer ↔ injector conversion
Dynamic Model Calibration




Adjusting historical production allocation
Adjusting the potential reservoir volume extension at different directions
Adjusting faults / channels / compartmentalization
Adjusting fracture model


Workflow



MRT @workflow


Examples



MRT @sample


See Also


Petroleum Industry / Upstream /  Production / Subsurface Production / Field Study & Modelling / Production Analysis

MRT @sample ] [ MRT @workflow ]

Permanent downhole gauges (PDG) ] Pressure Convolution  ] [ Pressure Deconvolution ] [ Multiwell Deconvolution (MDCV) ]

Radial Deconvolution (RDCV) ][ RDCV @model ]RDCV @sample ]

Cross-well Deconvolution (XDCV) ]XDCV @model ]XDCV @sample ] 

Material Balance Analysis ] [ Capacitance Resistance Model (CRM) ] Pressure Transient Analysis (PTA) ] 

  • No labels