Systems and methods for estimating pore pressure at source rocks

1. A pore pressure estimation system comprising:

a density logging tool configured to measure a bulk density of source rock at a vertical depth, wherein the density logging tool comprises a gamma ray source transmitting gamma rays into the source rocks-, and a detector configured to generate a density detection signal from a portion of the gamma rays that are scattered by the source rock, wherein a pore pressure estimation processor is operable to determine a total organic content (TOC) estimate of the source rock based on density detection signals;

a model module comprising a regional model for a region of source rock and a source rock model for source rock of a well bore, the source rock model of the model module comprising vitrinite ratio R o data for the source rock defining hydrocarbon maturity in the source rock, the regional model of the model module comprising regional data associated with the region of the source rock, the regional data comprising overburden gradient data defining overburden stress of the source rock in the region, a compaction velocity profile of the source rock in the region as a function of effective stress, and an unloading velocity profile of the source rock as a function of effective stress including pore overpressure and hydrocarbon maturity;

the pore pressure estimation processor communicably coupled to the density logging tool and the model module, and being operable to calculate an estimated pore pressure based on the overburden gradient data, the compaction velocity profile, the hydrocarbon maturity, and the unloading velocity profile, determine the TOC estimate of the source rock based on the bulk density at the vertical depth using the density logging tool, determine a correction factor based on (i) the TOC estimate and (ii) the vitrinite ratio R o data, and update the estimated pore pressure in real-time based on the correction factor.

2. The pore pressure estimation system of claim 1 , wherein the compaction velocity profile comprises a normal compaction trend curve representative of seismic velocity as a function of effective stress, the function calculated as

Y=Ax B ,

wherein Y is representative of the seismic velocity, x is representative of the effective stress, A is representative of a coefficient of the normal compaction trend curve, and B is an exponent of the normal compaction trend curve.

3. The pore pressure estimation system of claim 1 , wherein the unloading velocity profile comprises:

a maximum effective stress value σ max representative of a point of intersection between the unloading velocity profile and the compaction velocity profile; and

an unloading parameter U representative of an exponent of the unloading velocity profile when normalized to the maximum effective stress value σ max .

4. The pore pressure estimation system of claim 1 , wherein:

the estimated pore pressure is calculated based on a relation, the relation comprising

P

est

=

S

v

-

σ

max

[

1

σ

max

*

(

Δ

⁢

V

A

)

1

B

]

U

,

wherein S v is representative of the overburden gradient data multiplied by the vertical depth and a velocity difference ΔV is representative of a difference between a compressional velocity measured by the system and a surface compressional velocity from the regional data A is representative of a coefficient of a normal compaction trend curve associated with the compaction velocity profile, B is an exponent of the normal compaction trend curve, U is an unloading parameter representative of an exponent of the unloading velocity profile, and σ max is a maximum effective stress representative of a point of intersection between the unloading velocity profile and the compaction velocity profile; and

the velocity difference ΔV is measured in real time at the vertical depth by the system.

5. The pore pressure estimation system of claim 1 , wherein the unloading velocity profile comprises: a first unloading velocity profile associated with a high maturity hydrocarbon, the first unloading velocity profile comprising a first maximum effective stress value a max,1 representative of a first point of intersection between the first unloading velocity profile and the compaction velocity profile; and a second unloading velocity profile associated with a low maturity hydrocarbon, the second unloading velocity profile comprising a second maximum effective stress value a max,2 representative of a second point of intersection between the second unloading velocity profile and the compaction velocity profile.

6. The pore pressure estimation system of claim 5 , wherein, when the vitrinite ratio R o data indicates that the vertical depth is associated with the first unloading velocity profile associated with the high maturity hydrocarbon, the estimated pore pressure is calculated based on a relation, the relation comprising

P

est

=

S

v

-

σ

max

,

1

[

1

σ

max

,

1

*

(

Δ

⁢

V

A

)

1

B

]

U

,

where S v is representative of the overburden gradient data multiplied by the vertical depth and a velocity difference ΔV is representative of a difference between a compressional velocity measured by the system and a surface compressional velocity from the regional data; and

when the vitrinite ratio R o data indicates that the vertical depth is associated with the second unloading velocity profile associated with the low maturity hydrocarbon, the estimated pore pressure is calculated based on a relation, the relation comprising

P

est

=

S

v

-

σ

max

,

2

[

1

σ

max

,

2

*

(

Δ

⁢

V

A

)

1

B

]

U

.

7. The pore pressure estimation system of claim 6 , wherein the correction factor is determined based on whether the vitrinite ratio R o data at the vertical depth indicates that the vertical depth is associated with the first unloading velocity profile or the second unloading velocity profile.

8. The pore pressure estimation system of claim 1 , wherein the correction factor is added to the estimated pore pressure calculated based on the overburden gradient data, the compaction velocity profile, the hydrocarbon maturity, and the unloading velocity profile, and the correction factor is a function of the TOC estimate, and the TOC estimate is a function of the vitrinite R o data.

9. The pore pressure estimation system of claim 8 , wherein:

the vitrinite ratio R o data for the source rock defining the hydrocarbon maturity in the source rock comprises a cutoff value, the cutoff value reflective of a differentiation between a first hydrocarbon type in the source rock, associated with the vitrinite ratio R o data being less than the cutoff value, from a second hydrocarbon type in the source rock, associated with the vitrinite ratio R o data being greater than or equal to the cutoff value;

the correction factor comprises a first function of the TOC estimate when the vitrinite ratio R o data for the source rock at the vertical depth is beneath the cutoff value; and

the correction factor comprises a second function of the TOC estimate when the vitrinite ratio data for the source rock if the vitrinite ratio R o data for the source rock at the vertical depth is greater than or equal to the cutoff value.

10. The pore pressure estimation system of claim 1 , further comprising an acoustic transmitter and an acoustic receiver, wherein:

the acoustic transmitter is configured to transmit an acoustic signal that propagates through the source rock;

the acoustic receiver is configured to receive the acoustic signal after the acoustic signal propagates through the source rock;

the pore pressure estimation processor is communicably coupled to the acoustic transmitter and to the acoustic receiver to compute a compression wave delay time;

the estimated pore pressure is based on the compression wave delay time; and

the density logging tool, the acoustic transmitter, and the acoustic receiver are disposed in the well bore.

11. The pore pressure estimation system of claim 1 , the system further comprising a drill string and a drill bit, wherein:

the drill bit is disposed at an end of the drill string;

the drill bit is configured to carve the well bore through the source rock; and

the vertical depth at which the estimated pore pressure is estimated corresponds to the end of the drill string aligned with the source rock in the well bore.

12. The pore pressure estimation system of claim 11 , further comprising a mud weight system fluidly coupled to the drill string, wherein:

the mud weight system is configured to deliver a drilling mud having a mud weight into the well bore;

the mud weight of the drilling mud is based on the estimated pore pressure;

the mud weight system comprises a mud weight additive configured to change the mud weight based on a concentration of the mud weight additive in the mud weight; and

the pore pressure estimation processor is operable to compare the estimated pore pressure to the mud weight to determine whether the concentration of the mud weight additive satisfies a predetermined relationship when the mud weight is less than or equal to the estimated pore pressure.

13. The pore pressure estimation system of claim 12 , wherein in response to determining that the mud weight is less than the estimated pore pressure and that the predetermined relationship is not satisfied, the pore pressure estimation processor is configured to:

provide a mud weight notification;

control the concentration of the mud weight additive to dynamically update the mud weight in response to the estimated pore pressure and the mud weight notification; or

both.

14. A pore pressure estimation system comprising:

a density logging tool disposed in a well bore and is configured to measure a bulk density of source rock at a vertical depth, wherein the density logging tool comprises a gamma ray source transmitting gamma rays into the source rocks-, and a detector configured to generate a density detection signal from a portion of the gamma rays that are scattered by the source rock, wherein a pore pressure estimation processor is operable to determine a total organic content (TOC) estimate of the source rock based on density detection signals;

a model module comprising a regional model for a region of source rock and a source rock model for source rock of a well bore, the source rock model of the model module comprising vitrinite ratio R o data for the source rock defining hydrocarbon maturity in the source rock, the regional model of the model module comprising regional data associated with the region of the source rock, the regional data comprising overburden gradient data defining overburden stress of the source rock in the region, a compaction velocity profile of the source rock in the region as a function of effective stress, and an unloading velocity profile of the source rock as a function of effective stress including pore overpressure and hydrocarbon maturity; and

the pore pressure estimation processor communicably coupled to the density logging tool and the model module, being operable to calculate an estimated pore pressure based on the overburden gradient data, the compaction velocity profile, the hydrocarbon maturity and the unloading velocity profile, determine the TOC estimate of the source rock based on the bulk density at the vertical depth using the density logging tool, determine a correction factor based on (i) the TOC estimate and (ii) the vitrinite ratio R o data, and update the estimated pore pressure in real-time based on the correction factor such that the correction factor is added to the estimated pore pressure calculated based on the overburden gradient data, the compaction velocity profile, the hydrocarbon maturity, and the unloading velocity profile.

15. The pore pressure estimation system of claim 14 , wherein the compaction velocity profile comprises a normal compaction trend curve representative of seismic velocity as a function of effective stress, the function calculated as

Y=Ax B ,

wherein Y is representative of the seismic velocity, x is representative of the effective stress, A is representative of a coefficient of the normal compaction trend curve, and B is an exponent of the normal compaction trend curve.

16. The pore pressure estimation system of claim 14 , wherein the unloading velocity profile comprises:

a maximum effective stress value σ max representative of a point of intersection between the unloading velocity profile and the compaction velocity profile; and

an unloading parameter U representative of an exponent of the unloading velocity profile when normalized to the maximum effective stress value σ max .

17. The pore pressure estimation system of claim 14 , wherein the unloading velocity profile comprises: a first unloading velocity profile associated with a high maturity hydrocarbon, the first unloading velocity profile comprising a first maximum effective stress value a max,1 representative of a first point of intersection between the first unloading velocity profile and the compaction velocity profile; and a second unloading velocity profile associated with a low maturity hydrocarbon, the second unloading velocity profile comprising a second maximum effective stress value a max,2 representative of a second point of intersection between the second unloading velocity profile and the compaction velocity profile.

18. The pore pressure estimation system of claim 17 , wherein the correction factor is determined based on whether the vitrinite ratio R o data indicates that the vertical depth is associated with the first unloading velocity profile associated with the high maturity hydrocarbon or the second unloading velocity profile associated with the low maturity hydrocarbon.

19. A method comprising:

calculating, via a pore pressure estimation processor, an estimated pore pressure based on regional data of a regional model for a region of source rock of a well bore, the regional data of the regional model comprising overburden gradient data defining overburden stress of the source rock in the region, a compaction velocity profile of the source rock in the region as a function of effective stress, and an unloading velocity profile of the source rock as a function of effective stress and hydrocarbon maturity;

determining a total organic content (TOC) estimate of the source rock based on a bulk density at a vertical depth, wherein the bulk density at the vertical depth is estimated using a density logging tool that is configured to estimate the bulk density at the vertical depth, wherein the density logging tool comprises a gamma ray source transmitting gamma rays into the source rock, and a detector configured to generate a density detection signal from a portion of the gamma rays that are scattered by the source rock, wherein the pore pressure estimation processor is operable to determine the TOC estimate of the source rock based on density detection signals;

determining a correction factor based on (i) the TOC estimate and (ii) vitrinite ratio R 0 data for the source rock defining hydrocarbon maturity in the source rock; and

updating, via the pore pressure estimation processor, the estimated pore pressure in real-time based on the correction factor.